{"generated_at": "2026-10-28T19:48:17Z", "wall_clock_duration_ms": 37411.31, "headline_metrics": {"mjolnir_solve_rate_pct": 100.0, "ultra_bare_solve_rate_pct": 40.0, "mjolnir_cost_per_fix_usd": 0.001671, "ultra_always_cost_per_fix_usd": 0.003484, "cost_reduction_vs_ultra_always_pct": 52.0}, "arms": [{"strategy_id": "nano_alone", "label": "Nemotron-Nano (Bare)", "description": "Fast & cheap 1-shot attempt without live docs or escalation.", "total_tasks": 10, "solved_count": 1, "solve_rate_pct": 10.0, "api_shift_solved": "0/6", "logic_solved": "1/4", "total_cost_usd": 0.00033, "cost_per_verified_fix_usd": 0.00033, "avg_latency_ms": 744.5, "total_tokens": 3163, "tavily_calls": 0, "receipts": [{"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 4.5e-05, "total_latency_ms": 769.73, "total_tokens": 424, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "final_patch_sha256": "f39e2e2866059b80", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 258, "completion_tokens": 166, "total_tokens": 424, "latency_ms": 210.01, "cost_usd": 4.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 251.37, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "f39e2e2866059b80", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": ".EE\n======================================================================\nERROR: test_serialize_excludes_none (__main__.TestSchemaGuard.test_serialize_excludes_none)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_p65ns4kj\\test_solution.py\", line 6, in test_serialize_excludes_none\n res = serialize_user(' Alice ', 100, None)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_p65ns4kj\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n======================================================================\nERROR: test_serialize_with_tag (__main__.TestSchemaGuard.test_serialize_with_tag)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_p65ns4kj\\test_solution.py\", line 9, in test_serialize_with_tag\n res = serialize_user('Bob', 50, 'admin')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_p65ns4kj\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n----------------------------------------------------------------------\nRan 3 tests in 0.003s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'model_dump'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "model_dump", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'model_dump'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='model_dump')"}}}]}, {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.9e-05, "total_latency_ms": 744.38, "total_tokens": 289, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "10337aa2fabaceb5", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 194, "completion_tokens": 95, "total_tokens": 289, "latency_ms": 210.01, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 277.17, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "10337aa2fabaceb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "EE\n======================================================================\nERROR: test_full_stream (__main__.TestNebiusSSE.test_full_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8uyyvbs1\\test_solution.py\", line 6, in test_full_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '0')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8uyyvbs1\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n======================================================================\nERROR: test_resumed_stream (__main__.TestNebiusSSE.test_resumed_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8uyyvbs1\\test_solution.py\", line 9, in test_resumed_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '1')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8uyyvbs1\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'create_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "create_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'create_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='create_stream')"}}}]}, {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.8e-05, "total_latency_ms": 727.62, "total_tokens": 279, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "final_patch_sha256": "16d9f3cfffc3ba9d", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 184, "completion_tokens": 95, "total_tokens": 279, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 269.77, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "16d9f3cfffc3ba9d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_preserves_insertion_order_and_sums (__main__.TestFrameFlow.test_preserves_insertion_order_and_sums)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_oaldfgng\\test_solution.py\", line 11, in test_preserves_insertion_order_and_sums\n res = summarize_region_spend(data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_oaldfgng\\solution.py\", line 5, in summarize_region_spend\n return df.group_by('region').sum('cost')\n ^^^^^^^^^^^\nAttributeError: 'DataFrame' object has no attribute 'group_by'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'group_by'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "group_by", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'group_by'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='group_by')"}}}]}, {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.9e-05, "total_latency_ms": 748.09, "total_tokens": 287, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "final_patch_sha256": "c177115bdce9644e", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 187, "completion_tokens": 100, "total_tokens": 287, "latency_ms": 210.01, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 291.38, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "c177115bdce9644e", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_hybrid_ranking (__main__.TestVecStore.test_hybrid_ranking)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_0y9rhxgi\\test_solution.py\", line 11, in test_hybrid_ranking\n res = hybrid_retrieve(docs, [0.1, 0.2], 0.8, k=2)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_0y9rhxgi\\solution.py\", line 5, in hybrid_retrieve\n return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n ^^^^^^^^^^^^^^^^^\nAttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\n\n----------------------------------------------------------------------\nRan 1 test in 0.004s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'hybrid_search'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "hybrid_search", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='hybrid_search')"}}}]}, {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.8e-05, "total_latency_ms": 793.15, "total_tokens": 281, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "final_patch_sha256": "cbc76ffcb4bd4531", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 186, "completion_tokens": 95, "total_tokens": 281, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 289.38, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "cbc76ffcb4bd4531", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_valid_and_invalid_signature (__main__.TestCryptoSeal.test_valid_and_invalid_signature)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_udvdbar9\\test_solution.py\", line 9, in test_valid_and_invalid_signature\n self.assertTrue(verify_webhook_envelope(body, sig, secret))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_udvdbar9\\solution.py\", line 4, in verify_webhook_envelope\n return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'cryptoseal' has no attribute 'verify_signature'\n\n----------------------------------------------------------------------\nRan 1 test in 0.001s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_signature'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_signature", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_signature'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_signature')"}}}]}, {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 3e-05, "total_latency_ms": 729.94, "total_tokens": 300, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "final_patch_sha256": "39bbe1b9bf86b2c3", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 197, "completion_tokens": 103, "total_tokens": 300, "latency_ms": 210.01, "cost_usd": 3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 262.59, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "39bbe1b9bf86b2c3", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_j1ktpmd2\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_j1ktpmd2\\solution.py\", line 5, in dispatch_agent_tool\n reg.register(tool_name, fn)\n ^^^^^^^^^^^^\nAttributeError: 'ToolRegistryV2' object has no attribute 'register'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'register'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "register", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'register'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='register')"}}}]}, {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 3.3e-05, "total_latency_ms": 755.67, "total_tokens": 321, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "final_patch_sha256": "aedf55a4f3a22eb5", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 203, "completion_tokens": 118, "total_tokens": 321, "latency_ms": 210.01, "cost_usd": 3.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 276.2, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "aedf55a4f3a22eb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "raw_stdout": "", "raw_stderr": "F..\n======================================================================\nFAIL: test_boundary_scale_down_and_floor (__main__.TestRateGovernor.test_boundary_scale_down_and_floor)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ac_3cyr0\\test_solution.py\", line 10, in test_boundary_scale_down_and_floor\n self.assertEqual(evaluate_window_limit(110.0, 100.0, 0.20), 100.0)\nAssertionError: 73.33 != 100.0\n\n----------------------------------------------------------------------\nRan 3 tests in 0.001s\n\nFAILED (failures=1)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "73.33 != 100.0", "failing_location": "test_solution.py:L10 in test_boundary_scale_down_and_floor", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L10 in test_boundary_scale_down_and_floor\nFAILURE : AssertionError: 73.33 != 100.0\nDIAGNOSIS: REASONING_GAP"}}}]}, {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 4.3e-05, "total_latency_ms": 739.21, "total_tokens": 380, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "final_patch_sha256": "756e53b47df81b92", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 208, "completion_tokens": 172, "total_tokens": 380, "latency_ms": 210.01, "cost_usd": 4.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 266.5, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_nhay_m4z\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_nhay_m4z\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.001s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}]}, {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.8e-05, "total_latency_ms": 709.59, "total_tokens": 275, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "final_patch_sha256": "0a0de19e1ebe7219", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 180, "completion_tokens": 95, "total_tokens": 275, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 255.51, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "0a0de19e1ebe7219", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_three_way_equal_split_preserves_sum (__main__.TestExactLedger.test_three_way_equal_split_preserves_sum)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_1ngaxx8z\\test_solution.py\", line 7, in test_three_way_equal_split_preserves_sum\n self.assertEqual(res, [34, 33, 33])\nAssertionError: Lists differ: [33, 33, 33] != [34, 33, 33]\n\nFirst differing element 0:\n33\n34\n\n- [33, 33, 33]\n+ [34, 33, 33]\n\n======================================================================\nFAIL: test_weighted_remainder_tiebreak (__main__.TestExactLedger.test_weighted_remainder_tiebreak)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_1ngaxx8z\\test_solution.py\", line 11, in test_weighted_remainder_tiebreak\n self.assertEqual(res, [4, 3, 3])\nAssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\n\nFirst differing element 0:\n3\n4\n\n- [3, 3, 3]\n+ [4, 3, 3]\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}}}]}, {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "nano_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 3.7e-05, "total_latency_ms": 727.58, "total_tokens": 327, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 183, "completion_tokens": 144, "total_tokens": 327, "latency_ms": 210.01, "cost_usd": 3.7e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 257.76, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}]}, {"strategy_id": "ultra_alone", "label": "Nemotron-Ultra (Bare)", "description": "Always calls largest frontier model without live Tavily docs.", "total_tasks": 10, "solved_count": 4, "solve_rate_pct": 40.0, "api_shift_solved": "0/6", "logic_solved": "4/4", "total_cost_usd": 0.010451, "cost_per_verified_fix_usd": 0.002613, "avg_latency_ms": 1707.2, "total_tokens": 4223, "tavily_calls": 0, "receipts": [{"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.001249, "total_latency_ms": 1732.03, "total_tokens": 519, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "final_patch_sha256": "f39e2e2866059b80", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 258, "completion_tokens": 261, "total_tokens": 519, "latency_ms": 1180.01, "cost_usd": 0.001249, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 259.57, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "f39e2e2866059b80", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": ".EE\n======================================================================\nERROR: test_serialize_excludes_none (__main__.TestSchemaGuard.test_serialize_excludes_none)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_2uky0yet\\test_solution.py\", line 6, in test_serialize_excludes_none\n res = serialize_user(' Alice ', 100, None)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_2uky0yet\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n======================================================================\nERROR: test_serialize_with_tag (__main__.TestSchemaGuard.test_serialize_with_tag)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_2uky0yet\\test_solution.py\", line 9, in test_serialize_with_tag\n res = serialize_user('Bob', 50, 'admin')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_2uky0yet\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n----------------------------------------------------------------------\nRan 3 tests in 0.004s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'model_dump'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "model_dump", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'model_dump'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='model_dump')"}}}]}, {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000917, "total_latency_ms": 1704.76, "total_tokens": 384, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "10337aa2fabaceb5", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 194, "completion_tokens": 190, "total_tokens": 384, "latency_ms": 1180.01, "cost_usd": 0.000917, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 257.64, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "10337aa2fabaceb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "EE\n======================================================================\nERROR: test_full_stream (__main__.TestNebiusSSE.test_full_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_mrezolq1\\test_solution.py\", line 6, in test_full_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '0')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_mrezolq1\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n======================================================================\nERROR: test_resumed_stream (__main__.TestNebiusSSE.test_resumed_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_mrezolq1\\test_solution.py\", line 9, in test_resumed_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '1')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_mrezolq1\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'create_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "create_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'create_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='create_stream')"}}}]}, {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000869, "total_latency_ms": 1710.41, "total_tokens": 364, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "final_patch_sha256": "16d9f3cfffc3ba9d", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 184, "completion_tokens": 180, "total_tokens": 364, "latency_ms": 1180.01, "cost_usd": 0.000869, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 272.28, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "16d9f3cfffc3ba9d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_preserves_insertion_order_and_sums (__main__.TestFrameFlow.test_preserves_insertion_order_and_sums)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_f8etnc3m\\test_solution.py\", line 11, in test_preserves_insertion_order_and_sums\n res = summarize_region_spend(data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_f8etnc3m\\solution.py\", line 5, in summarize_region_spend\n return df.group_by('region').sum('cost')\n ^^^^^^^^^^^\nAttributeError: 'DataFrame' object has no attribute 'group_by'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'group_by'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "group_by", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'group_by'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='group_by')"}}}]}, {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000926, "total_latency_ms": 1688.81, "total_tokens": 382, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "final_patch_sha256": "c177115bdce9644e", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 187, "completion_tokens": 195, "total_tokens": 382, "latency_ms": 1180.01, "cost_usd": 0.000926, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 261.25, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "c177115bdce9644e", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_hybrid_ranking (__main__.TestVecStore.test_hybrid_ranking)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9sxbphl7\\test_solution.py\", line 11, in test_hybrid_ranking\n res = hybrid_retrieve(docs, [0.1, 0.2], 0.8, k=2)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9sxbphl7\\solution.py\", line 5, in hybrid_retrieve\n return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n ^^^^^^^^^^^^^^^^^\nAttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\n\n----------------------------------------------------------------------\nRan 1 test in 0.003s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'hybrid_search'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "hybrid_search", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='hybrid_search')"}}}]}, {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000886, "total_latency_ms": 1717.37, "total_tokens": 370, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "final_patch_sha256": "cbc76ffcb4bd4531", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 186, "completion_tokens": 184, "total_tokens": 370, "latency_ms": 1180.01, "cost_usd": 0.000886, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 279.3, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "cbc76ffcb4bd4531", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_valid_and_invalid_signature (__main__.TestCryptoSeal.test_valid_and_invalid_signature)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5y0ba1ib\\test_solution.py\", line 9, in test_valid_and_invalid_signature\n self.assertTrue(verify_webhook_envelope(body, sig, secret))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5y0ba1ib\\solution.py\", line 4, in verify_webhook_envelope\n return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'cryptoseal' has no attribute 'verify_signature'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_signature'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_signature", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_signature'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_signature')"}}}]}, {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000949, "total_latency_ms": 1707.09, "total_tokens": 395, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "final_patch_sha256": "39bbe1b9bf86b2c3", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 197, "completion_tokens": 198, "total_tokens": 395, "latency_ms": 1180.01, "cost_usd": 0.000949, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 267.56, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "39bbe1b9bf86b2c3", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8m93kz44\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8m93kz44\\solution.py\", line 5, in dispatch_agent_tool\n reg.register(tool_name, fn)\n ^^^^^^^^^^^^\nAttributeError: 'ToolRegistryV2' object has no attribute 'register'\n\n----------------------------------------------------------------------\nRan 1 test in 0.003s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'register'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "register", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'register'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='register')"}}}]}, {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "ultra_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.001061, "total_latency_ms": 1705.25, "total_tokens": 430, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "final_patch_sha256": "725f31978394eac0", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 203, "completion_tokens": 227, "total_tokens": 430, "latency_ms": 1180.01, "cost_usd": 0.001061, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 248.51, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "725f31978394eac0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "ultra_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.001312, "total_latency_ms": 1703.57, "total_tokens": 503, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,21 @@+import heapq\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ heap = [t for t, d in indeg.items() if d == 0]\n+ heapq.heapify(heap)\n order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n+ while heap:\n+ curr = heapq.heappop(heap)\n+ order.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ heapq.heappush(heap, nxt)\n+ if len(order) != len(tasks):\n+ raise ValueError('Cycle detected')\n return order\n", "final_patch_sha256": "4480a72e2cf8136d", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 208, "completion_tokens": 295, "total_tokens": 503, "latency_ms": 1180.01, "cost_usd": 0.001312, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 261.25, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "4480a72e2cf8136d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,21 @@+import heapq\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ heap = [t for t, d in indeg.items() if d == 0]\n+ heapq.heapify(heap)\n order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n+ while heap:\n+ curr = heapq.heappop(heap)\n+ order.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ heapq.heappush(heap, nxt)\n+ if len(order) != len(tasks):\n+ raise ValueError('Cycle detected')\n return order\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "ultra_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.001202, "total_latency_ms": 1708.37, "total_tokens": 454, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "final_patch_sha256": "d1f3381a6615115b", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 180, "completion_tokens": 274, "total_tokens": 454, "latency_ms": 1180.01, "cost_usd": 0.001202, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 272.34, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "d1f3381a6615115b", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "ultra_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.00108, "total_latency_ms": 1694.1, "total_tokens": 422, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 183, "completion_tokens": 239, "total_tokens": 422, "latency_ms": 1180.01, "cost_usd": 0.00108, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 252.94, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}]}, {"strategy_id": "nano_tavily", "label": "Nemotron-Nano + Tavily", "description": "Small model paired with 3-stage Tavily documentation retrieval.", "total_tasks": 10, "solved_count": 6, "solve_rate_pct": 60.0, "api_shift_solved": "5/6", "logic_solved": "1/4", "total_cost_usd": 0.020373, "cost_per_verified_fix_usd": 0.003396, "avg_latency_ms": 934.2, "total_tokens": 3769, "tavily_calls": 10, "receipts": [{"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.00205, "total_latency_ms": 922.27, "total_tokens": 500, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "final_patch_sha256": "58bf23a0fc7192d1", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 332, "completion_tokens": 168, "total_tokens": 500, "latency_ms": 210.01, "cost_usd": 5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": {"triggered": true, "query": "SchemaGuard v3 BaseSchema dict model_dump_strict exclude_none migration 2026", "target_domains": ["docs.pydantic.dev", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pydantic.dev/latest/migration/#model-dump-strict", "https://github.com/schemaguard/schemaguard/releases/tag/v3.0.0"], "extracted_markdown": "### SchemaGuard v3.0 Breaking Change (2026 Release)\n- Removed `.dict()` and `.model_dump()` from `BaseSchema`.\n- Replacement: Call `instance.model_dump_strict(*, exclude_none: bool = False) -> dict`.\n- Note: `exclude_none` is a keyword-only argument.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 265.83, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "58bf23a0fc7192d1", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002034, "total_latency_ms": 924.86, "total_tokens": 363, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "840a90d4123949bf", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 265, "completion_tokens": 98, "total_tokens": 363, "latency_ms": 210.01, "cost_usd": 3.4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": {"triggered": true, "query": "nebius_sse connect_stream open_resumable_stream resume_cursor API reference", "target_domains": ["docs.nebius.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nebius.com/token-factory/streaming-sse-v2"], "extracted_markdown": "### `nebius_sse` v2.0 Migration Guide\n- Deprecated and removed: `nebius_sse.connect_stream(endpoint, last_event_id=...)`\n- New signature: `nebius_sse.open_resumable_stream(endpoint: str, *, resume_cursor: str = '0', timeout_ms: int = 5000)`", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 266.39, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "840a90d4123949bf", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002033, "total_latency_ms": 907.7, "total_tokens": 356, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "final_patch_sha256": "625b8722368e82a0", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 261, "completion_tokens": 95, "total_tokens": 356, "latency_ms": 210.02, "cost_usd": 3.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": {"triggered": true, "query": "frameflow DataFrame groupby group_by_key maintain_order sum_column 2026", "target_domains": ["docs.pola.rs", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pola.rs/releases/upgrade/2026-groupby-key/"], "extracted_markdown": "### FrameFlow 2026 Breaking API Change\n- `df.groupby()` and `.agg_sum()` were removed.\n- Use `df.group_by_key(key_col: str, *, maintain_order: bool = False)` followed by `.sum_column(target_col: str)`.\n- Pass `maintain_order=True` to preserve first-seen key order.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 257.48, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "625b8722368e82a0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002034, "total_latency_ms": 943.5, "total_tokens": 361, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "final_patch_sha256": "d8a10177a12c519c", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 257, "completion_tokens": 104, "total_tokens": 361, "latency_ms": 210.02, "cost_usd": 3.4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": {"triggered": true, "query": "vecstore v4 VectorIndex query query_hybrid dense_vector fusion_weight top_k", "target_domains": ["docs.pinecone.io", "qdrant.tech"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://qdrant.tech/documentation/concepts/hybrid-queries-v4/"], "extracted_markdown": "### VecStore v4.0 Migration Note\n- Removed `VectorIndex.query(vec, alpha=..., limit=...)`.\n- Replaced with keyword-only `VectorIndex.query_hybrid(*, dense_vector: list[float], fusion_weight: float = 0.5, top_k: int = 3) -> list[str]`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 277.25, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "d8a10177a12c519c", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002035, "total_latency_ms": 915.58, "total_tokens": 363, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "final_patch_sha256": "ef1ea68d03e68178", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 253, "completion_tokens": 110, "total_tokens": 363, "latency_ms": 210.01, "cost_usd": 3.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": {"triggered": true, "query": "cryptoseal verify_hmac verify_envelope_v2 payload_bytes signature_hex key_bytes", "target_domains": ["cryptography.io", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://cryptography.io/en/latest/changelog/#v2026-envelope-v2"], "extracted_markdown": "### CryptoSeal 2026 Security Upgrade\n- `verify_hmac(str, str, str)` has been removed to prevent encoding ambiguity.\n- Use `cryptoseal.verify_envelope_v2(*, payload_bytes: bytes, signature_hex: str, key_bytes: bytes) -> bool`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 261.18, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "ef1ea68d03e68178", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.00204, "total_latency_ms": 911.67, "total_tokens": 427, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n", "final_patch_sha256": "ceae088d87d6d46a", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 307, "completion_tokens": 120, "total_tokens": 427, "latency_ms": 210.01, "cost_usd": 4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": {"triggered": true, "query": "nemo_toolspec ToolRegistryV2 register_callable invoke_strict int_fields", "target_domains": ["docs.nvidia.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nvidia.com/nemo/agent-toolkit/2026/tool-registry-v2.html"], "extracted_markdown": "### NeMo ToolSpec v2 (`ToolRegistryV2`)\n- Replaced `add_tool` / `execute` with keyword-only methods:\n 1. `reg.register_callable(*, tool_name: str, fn, int_fields: list[str] = None)`\n 2. `reg.invoke_strict(*, tool_name: str, payload: dict)`\n- IMPORTANT: `invoke_strict` raises `TypeError` if any key in `int_fields` is still a `str`; caller must cast `int(payload[k])` prior to `invoke_strict`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 247.71, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "ceae088d87d6d46a", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ot_vpnzz\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ot_vpnzz\\solution.py\", line 6, in dispatch_agent_tool\n return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ot_vpnzz\\nemo_toolspec.py\", line 12, in invoke_strict\n raise TypeError(f'Field {field} must be coerced to int before invoke_strict')\nTypeError: Field nodes must be coerced to int before invoke_strict\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "TypeError", "error_message": "Field nodes must be coerced to int before invoke_strict", "failing_location": "nemo_toolspec.py:L12 in invoke_strict", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : nemo_toolspec.py:L12 in invoke_strict\nFAILURE : TypeError: Field nodes must be coerced to int before invoke_strict\nDIAGNOSIS: REASONING_GAP"}}}]}, {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "nano_tavily", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.002035, "total_latency_ms": 920.56, "total_tokens": 355, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "final_patch_sha256": "aedf55a4f3a22eb5", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 237, "completion_tokens": 118, "total_tokens": 355, "latency_ms": 210.01, "cost_usd": 3.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": {"triggered": true, "query": "rate limit token bucket sliding window algorithm generic", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Token_bucket"], "extracted_markdown": "Generic token bucket rate limiting article (unrelated to exact floor/ceiling invariant).", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 274.8, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "aedf55a4f3a22eb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "raw_stdout": "", "raw_stderr": "F..\n======================================================================\nFAIL: test_boundary_scale_down_and_floor (__main__.TestRateGovernor.test_boundary_scale_down_and_floor)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_wvj5ifo2\\test_solution.py\", line 10, in test_boundary_scale_down_and_floor\n self.assertEqual(evaluate_window_limit(110.0, 100.0, 0.20), 100.0)\nAssertionError: 73.33 != 100.0\n\n----------------------------------------------------------------------\nRan 3 tests in 0.001s\n\nFAILED (failures=1)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "73.33 != 100.0", "failing_location": "test_solution.py:L10 in test_boundary_scale_down_and_floor", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L10 in test_boundary_scale_down_and_floor\nFAILURE : AssertionError: 73.33 != 100.0\nDIAGNOSIS: REASONING_GAP"}}}]}, {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "nano_tavily", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.002045, "total_latency_ms": 932.45, "total_tokens": 408, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "final_patch_sha256": "756e53b47df81b92", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 236, "completion_tokens": 172, "total_tokens": 408, "latency_ms": 210.01, "cost_usd": 4.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": {"triggered": true, "query": "topological sort graph theory overview", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Topological_sorting"], "extracted_markdown": "Standard FIFO Kahn's algorithm overview without heap tie-breaking.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 288.52, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_g7oeeutp\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_g7oeeutp\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}]}, {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "nano_tavily", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.002029, "total_latency_ms": 1027.24, "total_tokens": 291, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "final_patch_sha256": "0a0de19e1ebe7219", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 196, "completion_tokens": 95, "total_tokens": 291, "latency_ms": 210.02, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": {"triggered": true, "query": "proportional allocation rounding", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Largest_remainder_method"], "extracted_markdown": "General overview of rounding methods.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 345.36, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "0a0de19e1ebe7219", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_three_way_equal_split_preserves_sum (__main__.TestExactLedger.test_three_way_equal_split_preserves_sum)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_hn43w513\\test_solution.py\", line 7, in test_three_way_equal_split_preserves_sum\n self.assertEqual(res, [34, 33, 33])\nAssertionError: Lists differ: [33, 33, 33] != [34, 33, 33]\n\nFirst differing element 0:\n33\n34\n\n- [33, 33, 33]\n+ [34, 33, 33]\n\n======================================================================\nFAIL: test_weighted_remainder_tiebreak (__main__.TestExactLedger.test_weighted_remainder_tiebreak)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_hn43w513\\test_solution.py\", line 11, in test_weighted_remainder_tiebreak\n self.assertEqual(res, [4, 3, 3])\nAssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\n\nFirst differing element 0:\n3\n4\n\n- [3, 3, 3]\n+ [4, 3, 3]\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}}}]}, {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002038, "total_latency_ms": 936.07, "total_tokens": 345, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 201, "completion_tokens": 144, "total_tokens": 345, "latency_ms": 210.01, "cost_usd": 3.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": {"triggered": true, "query": "LRU cache eviction policy", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Cache_replacement_policies"], "extracted_markdown": "Standard LRU cache overview.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 276.18, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}]}, {"strategy_id": "ultra_tavily_always", "label": "Nemotron-Ultra + Always-On Tavily", "description": "Largest model + indiscriminate web search on every task.", "total_tasks": 10, "solved_count": 9, "solve_rate_pct": 90.0, "api_shift_solved": "6/6", "logic_solved": "3/4", "total_cost_usd": 0.031357, "cost_per_verified_fix_usd": 0.003484, "avg_latency_ms": 2444.2, "total_tokens": 4851, "tavily_calls": 10, "receipts": [{"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003345, "total_latency_ms": 1957.91, "total_tokens": 595, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "final_patch_sha256": "58bf23a0fc7192d1", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 332, "completion_tokens": 263, "total_tokens": 595, "latency_ms": 1180.02, "cost_usd": 0.001345, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": {"triggered": true, "query": "SchemaGuard v3 BaseSchema dict model_dump_strict exclude_none migration 2026", "target_domains": ["docs.pydantic.dev", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pydantic.dev/latest/migration/#model-dump-strict", "https://github.com/schemaguard/schemaguard/releases/tag/v3.0.0"], "extracted_markdown": "### SchemaGuard v3.0 Breaking Change (2026 Release)\n- Removed `.dict()` and `.model_dump()` from `BaseSchema`.\n- Replacement: Call `instance.model_dump_strict(*, exclude_none: bool = False) -> dict`.\n- Note: `exclude_none` is a keyword-only argument.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 307.96, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "58bf23a0fc7192d1", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003013, "total_latency_ms": 1845.96, "total_tokens": 458, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "840a90d4123949bf", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 265, "completion_tokens": 193, "total_tokens": 458, "latency_ms": 1180.01, "cost_usd": 0.001013, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": {"triggered": true, "query": "nebius_sse connect_stream open_resumable_stream resume_cursor API reference", "target_domains": ["docs.nebius.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nebius.com/token-factory/streaming-sse-v2"], "extracted_markdown": "### `nebius_sse` v2.0 Migration Guide\n- Deprecated and removed: `nebius_sse.connect_stream(endpoint, last_event_id=...)`\n- New signature: `nebius_sse.open_resumable_stream(endpoint: str, *, resume_cursor: str = '0', timeout_ms: int = 5000)`", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 244.51, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "840a90d4123949bf", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.00299, "total_latency_ms": 1832.44, "total_tokens": 449, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "final_patch_sha256": "625b8722368e82a0", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 261, "completion_tokens": 188, "total_tokens": 449, "latency_ms": 1180.01, "cost_usd": 0.00099, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": {"triggered": true, "query": "frameflow DataFrame groupby group_by_key maintain_order sum_column 2026", "target_domains": ["docs.pola.rs", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pola.rs/releases/upgrade/2026-groupby-key/"], "extracted_markdown": "### FrameFlow 2026 Breaking API Change\n- `df.groupby()` and `.agg_sum()` were removed.\n- Use `df.group_by_key(key_col: str, *, maintain_order: bool = False)` followed by `.sum_column(target_col: str)`.\n- Pass `maintain_order=True` to preserve first-seen key order.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 236.48, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "625b8722368e82a0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003025, "total_latency_ms": 1945.19, "total_tokens": 456, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "final_patch_sha256": "d8a10177a12c519c", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 257, "completion_tokens": 199, "total_tokens": 456, "latency_ms": 1180.01, "cost_usd": 0.001025, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": {"triggered": true, "query": "vecstore v4 VectorIndex query query_hybrid dense_vector fusion_weight top_k", "target_domains": ["docs.pinecone.io", "qdrant.tech"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://qdrant.tech/documentation/concepts/hybrid-queries-v4/"], "extracted_markdown": "### VecStore v4.0 Migration Note\n- Removed `VectorIndex.query(vec, alpha=..., limit=...)`.\n- Replaced with keyword-only `VectorIndex.query_hybrid(*, dense_vector: list[float], fusion_weight: float = 0.5, top_k: int = 3) -> list[str]`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 309.96, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "d8a10177a12c519c", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003042, "total_latency_ms": 2339.24, "total_tokens": 458, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "final_patch_sha256": "ef1ea68d03e68178", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 253, "completion_tokens": 205, "total_tokens": 458, "latency_ms": 1180.01, "cost_usd": 0.001042, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": {"triggered": true, "query": "cryptoseal verify_hmac verify_envelope_v2 payload_bytes signature_hex key_bytes", "target_domains": ["cryptography.io", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://cryptography.io/en/latest/changelog/#v2026-envelope-v2"], "extracted_markdown": "### CryptoSeal 2026 Security Upgrade\n- `verify_hmac(str, str, str)` has been removed to prevent encoding ambiguity.\n- Use `cryptoseal.verify_envelope_v2(*, payload_bytes: bytes, signature_hex: str, key_bytes: bytes) -> bool`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 454.72, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "ef1ea68d03e68178", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.001s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003272, "total_latency_ms": 2301.84, "total_tokens": 558, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,9 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ coerced = dict(raw_args)\n+ for k in int_keys:\n+ if k in coerced and coerced[k] is not None:\n+ coerced[k] = int(coerced[k])\n+ return reg.invoke_strict(tool_name=tool_name, payload=coerced)\n", "final_patch_sha256": "70a900879c9cdffa", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 307, "completion_tokens": 251, "total_tokens": 558, "latency_ms": 1180.01, "cost_usd": 0.001272, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": {"triggered": true, "query": "nemo_toolspec ToolRegistryV2 register_callable invoke_strict int_fields", "target_domains": ["docs.nvidia.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nvidia.com/nemo/agent-toolkit/2026/tool-registry-v2.html"], "extracted_markdown": "### NeMo ToolSpec v2 (`ToolRegistryV2`)\n- Replaced `add_tool` / `execute` with keyword-only methods:\n 1. `reg.register_callable(*, tool_name: str, fn, int_fields: list[str] = None)`\n 2. `reg.invoke_strict(*, tool_name: str, payload: dict)`\n- IMPORTANT: `invoke_strict` raises `TypeError` if any key in `int_fields` is still a `str`; caller must cast `int(payload[k])` prior to `invoke_strict`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 434.14, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "70a900879c9cdffa", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,9 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ coerced = dict(raw_args)\n+ for k in int_keys:\n+ if k in coerced and coerced[k] is not None:\n+ coerced[k] = int(coerced[k])\n+ return reg.invoke_strict(tool_name=tool_name, payload=coerced)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003102, "total_latency_ms": 2198.93, "total_tokens": 464, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "final_patch_sha256": "725f31978394eac0", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 237, "completion_tokens": 227, "total_tokens": 464, "latency_ms": 1180.04, "cost_usd": 0.001102, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": {"triggered": true, "query": "rate limit token bucket sliding window algorithm generic", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Token_bucket"], "extracted_markdown": "Generic token bucket rate limiting article (unrelated to exact floor/ceiling invariant).", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 459.75, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "725f31978394eac0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.003s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "ultra_tavily_always", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.003244, "total_latency_ms": 2053.8, "total_tokens": 503, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "final_patch_sha256": "756e53b47df81b92", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 236, "completion_tokens": 267, "total_tokens": 503, "latency_ms": 1180.01, "cost_usd": 0.001244, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": {"triggered": true, "query": "topological sort graph theory overview", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Topological_sorting"], "extracted_markdown": "Standard FIFO Kahn's algorithm overview without heap tie-breaking.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 295.54, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5ajljpb1\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5ajljpb1\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}]}, {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003222, "total_latency_ms": 2917.54, "total_tokens": 470, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "final_patch_sha256": "d1f3381a6615115b", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 196, "completion_tokens": 274, "total_tokens": 470, "latency_ms": 1180.13, "cost_usd": 0.001222, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": {"triggered": true, "query": "proportional allocation rounding", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Largest_remainder_method"], "extracted_markdown": "General overview of rounding methods.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 1184.52, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "d1f3381a6615115b", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003102, "total_latency_ms": 5049.42, "total_tokens": 440, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 201, "completion_tokens": 239, "total_tokens": 440, "latency_ms": 1180.01, "cost_usd": 0.001102, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": {"triggered": true, "query": "LRU cache eviction policy", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Cache_replacement_policies"], "extracted_markdown": "Standard LRU cache overview.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 675.78, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.001s\n\nOK\n", "error_receipt": null}}]}]}, {"strategy_id": "mjolnir_2d_ladder", "label": "MJOLNIR 2D Escalation Engine", "description": "Selective Error-Triggered Tavily + Tiered Nemotron (Nano -> Super -> Ultra).", "total_tasks": 10, "solved_count": 10, "solve_rate_pct": 100.0, "api_shift_solved": "6/6", "logic_solved": "4/4", "total_cost_usd": 0.016711, "cost_per_verified_fix_usd": 0.001671, "avg_latency_ms": 1778.5, "total_tokens": 7579, "tavily_calls": 6, "receipts": [{"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002095, "total_latency_ms": 2396.66, "total_tokens": 927, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "final_patch_sha256": "58bf23a0fc7192d1", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 258, "completion_tokens": 166, "total_tokens": 424, "latency_ms": 210.01, "cost_usd": 4.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 344.11, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "f39e2e2866059b80", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": ".EE\n======================================================================\nERROR: test_serialize_excludes_none (__main__.TestSchemaGuard.test_serialize_excludes_none)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9u022sg1\\test_solution.py\", line 6, in test_serialize_excludes_none\n res = serialize_user(' Alice ', 100, None)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9u022sg1\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n======================================================================\nERROR: test_serialize_with_tag (__main__.TestSchemaGuard.test_serialize_with_tag)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9u022sg1\\test_solution.py\", line 9, in test_serialize_with_tag\n res = serialize_user('Bob', 50, 'admin')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9u022sg1\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n----------------------------------------------------------------------\nRan 3 tests in 0.003s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'model_dump'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "model_dump", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'model_dump'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='model_dump')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 335, "completion_tokens": 168, "total_tokens": 503, "latency_ms": 210.01, "cost_usd": 5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": {"triggered": true, "query": "SchemaGuard v3 BaseSchema dict model_dump_strict exclude_none migration 2026", "target_domains": ["docs.pydantic.dev", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pydantic.dev/latest/migration/#model-dump-strict", "https://github.com/schemaguard/schemaguard/releases/tag/v3.0.0"], "extracted_markdown": "### SchemaGuard v3.0 Breaking Change (2026 Release)\n- Removed `.dict()` and `.model_dump()` from `BaseSchema`.\n- Replacement: Call `instance.model_dump_strict(*, exclude_none: bool = False) -> dict`.\n- Note: `exclude_none` is a keyword-only argument.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 583.44, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "58bf23a0fc7192d1", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.001s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002063, "total_latency_ms": 1709.97, "total_tokens": 652, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "840a90d4123949bf", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 194, "completion_tokens": 95, "total_tokens": 289, "latency_ms": 210.01, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 344.1, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "10337aa2fabaceb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "EE\n======================================================================\nERROR: test_full_stream (__main__.TestNebiusSSE.test_full_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_bwebs943\\test_solution.py\", line 6, in test_full_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '0')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_bwebs943\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n======================================================================\nERROR: test_resumed_stream (__main__.TestNebiusSSE.test_resumed_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_bwebs943\\test_solution.py\", line 9, in test_resumed_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '1')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_bwebs943\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'create_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "create_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'create_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='create_stream')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 265, "completion_tokens": 98, "total_tokens": 363, "latency_ms": 210.01, "cost_usd": 3.4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": {"triggered": true, "query": "nebius_sse connect_stream open_resumable_stream resume_cursor API reference", "target_domains": ["docs.nebius.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nebius.com/token-factory/streaming-sse-v2"], "extracted_markdown": "### `nebius_sse` v2.0 Migration Guide\n- Deprecated and removed: `nebius_sse.connect_stream(endpoint, last_event_id=...)`\n- New signature: `nebius_sse.open_resumable_stream(endpoint: str, *, resume_cursor: str = '0', timeout_ms: int = 5000)`", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 401.74, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "840a90d4123949bf", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002061, "total_latency_ms": 1687.77, "total_tokens": 636, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "final_patch_sha256": "625b8722368e82a0", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 184, "completion_tokens": 95, "total_tokens": 279, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 361.23, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "16d9f3cfffc3ba9d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_preserves_insertion_order_and_sums (__main__.TestFrameFlow.test_preserves_insertion_order_and_sums)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_1c5h4dwi\\test_solution.py\", line 11, in test_preserves_insertion_order_and_sums\n res = summarize_region_spend(data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_1c5h4dwi\\solution.py\", line 5, in summarize_region_spend\n return df.group_by('region').sum('cost')\n ^^^^^^^^^^^\nAttributeError: 'DataFrame' object has no attribute 'group_by'\n\n----------------------------------------------------------------------\nRan 1 test in 0.003s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'group_by'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "group_by", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'group_by'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='group_by')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 262, "completion_tokens": 95, "total_tokens": 357, "latency_ms": 210.01, "cost_usd": 3.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": {"triggered": true, "query": "frameflow DataFrame groupby group_by_key maintain_order sum_column 2026", "target_domains": ["docs.pola.rs", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pola.rs/releases/upgrade/2026-groupby-key/"], "extracted_markdown": "### FrameFlow 2026 Breaking API Change\n- `df.groupby()` and `.agg_sum()` were removed.\n- Use `df.group_by_key(key_col: str, *, maintain_order: bool = False)` followed by `.sum_column(target_col: str)`.\n- Pass `maintain_order=True` to preserve first-seen key order.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 276.26, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "625b8722368e82a0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002063, "total_latency_ms": 1461.38, "total_tokens": 652, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "final_patch_sha256": "d8a10177a12c519c", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 187, "completion_tokens": 100, "total_tokens": 287, "latency_ms": 210.01, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 256.15, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "c177115bdce9644e", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_hybrid_ranking (__main__.TestVecStore.test_hybrid_ranking)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_du7f4fh6\\test_solution.py\", line 11, in test_hybrid_ranking\n res = hybrid_retrieve(docs, [0.1, 0.2], 0.8, k=2)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_du7f4fh6\\solution.py\", line 5, in hybrid_retrieve\n return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n ^^^^^^^^^^^^^^^^^\nAttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'hybrid_search'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "hybrid_search", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='hybrid_search')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 261, "completion_tokens": 104, "total_tokens": 365, "latency_ms": 210.01, "cost_usd": 3.4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": {"triggered": true, "query": "vecstore v4 VectorIndex query query_hybrid dense_vector fusion_weight top_k", "target_domains": ["docs.pinecone.io", "qdrant.tech"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://qdrant.tech/documentation/concepts/hybrid-queries-v4/"], "extracted_markdown": "### VecStore v4.0 Migration Note\n- Removed `VectorIndex.query(vec, alpha=..., limit=...)`.\n- Replaced with keyword-only `VectorIndex.query_hybrid(*, dense_vector: list[float], fusion_weight: float = 0.5, top_k: int = 3) -> list[str]`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 279.24, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "d8a10177a12c519c", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002063, "total_latency_ms": 1361.23, "total_tokens": 647, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "final_patch_sha256": "ef1ea68d03e68178", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 186, "completion_tokens": 95, "total_tokens": 281, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 253.83, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "cbc76ffcb4bd4531", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_valid_and_invalid_signature (__main__.TestCryptoSeal.test_valid_and_invalid_signature)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_s1zgdyes\\test_solution.py\", line 9, in test_valid_and_invalid_signature\n self.assertTrue(verify_webhook_envelope(body, sig, secret))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_s1zgdyes\\solution.py\", line 4, in verify_webhook_envelope\n return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'cryptoseal' has no attribute 'verify_signature'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_signature'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_signature", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_signature'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_signature')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 256, "completion_tokens": 110, "total_tokens": 366, "latency_ms": 210.01, "cost_usd": 3.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": {"triggered": true, "query": "cryptoseal verify_hmac verify_envelope_v2 payload_bytes signature_hex key_bytes", "target_domains": ["cryptography.io", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://cryptography.io/en/latest/changelog/#v2026-envelope-v2"], "extracted_markdown": "### CryptoSeal 2026 Security Upgrade\n- `verify_hmac(str, str, str)` has been removed to prevent encoding ambiguity.\n- Use `cryptoseal.verify_envelope_v2(*, payload_bytes: bytes, signature_hex: str, key_bytes: bytes) -> bool`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 248.95, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "ef1ea68d03e68178", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.004301, "total_latency_ms": 2483.13, "total_tokens": 1185, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "Rung 3 (Combined Axis): Nemotron-Super + Tavily Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,9 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ coerced = dict(raw_args)\n+ for k in int_keys:\n+ if k in coerced and coerced[k] is not None:\n+ coerced[k] = int(coerced[k])\n+ return reg.invoke_strict(tool_name=tool_name, payload=coerced)\n", "final_patch_sha256": "70a900879c9cdffa", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 197, "completion_tokens": 103, "total_tokens": 300, "latency_ms": 210.01, "cost_usd": 3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 278.42, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "39bbe1b9bf86b2c3", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_q1g08t3u\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_q1g08t3u\\solution.py\", line 5, in dispatch_agent_tool\n reg.register(tool_name, fn)\n ^^^^^^^^^^^^\nAttributeError: 'ToolRegistryV2' object has no attribute 'register'\n\n----------------------------------------------------------------------\nRan 1 test in 0.003s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'register'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "register", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'register'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='register')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 307, "completion_tokens": 120, "total_tokens": 427, "latency_ms": 210.02, "cost_usd": 4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": {"triggered": true, "query": "nemo_toolspec ToolRegistryV2 register_callable invoke_strict int_fields", "target_domains": ["docs.nvidia.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nvidia.com/nemo/agent-toolkit/2026/tool-registry-v2.html"], "extracted_markdown": "### NeMo ToolSpec v2 (`ToolRegistryV2`)\n- Replaced `add_tool` / `execute` with keyword-only methods:\n 1. `reg.register_callable(*, tool_name: str, fn, int_fields: list[str] = None)`\n 2. `reg.invoke_strict(*, tool_name: str, payload: dict)`\n- IMPORTANT: `invoke_strict` raises `TypeError` if any key in `int_fields` is still a `str`; caller must cast `int(payload[k])` prior to `invoke_strict`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 296.91, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "ceae088d87d6d46a", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_cyfrbcbi\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_cyfrbcbi\\solution.py\", line 6, in dispatch_agent_tool\n return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_cyfrbcbi\\nemo_toolspec.py\", line 12, in invoke_strict\n raise TypeError(f'Field {field} must be coerced to int before invoke_strict')\nTypeError: Field nodes must be coerced to int before invoke_strict\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "TypeError", "error_message": "Field nodes must be coerced to int before invoke_strict", "failing_location": "nemo_toolspec.py:L12 in invoke_strict", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : nemo_toolspec.py:L12 in invoke_strict\nFAILURE : TypeError: Field nodes must be coerced to int before invoke_strict\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 3, "stage_label": "Rung 3 (Combined Axis): Nemotron-Super + Tavily Docs", "tier": "super", "used_tavily": true, "nebius_call": {"tier": "super", "model_id": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B", "prompt_tokens": 302, "completion_tokens": 156, "total_tokens": 458, "latency_ms": 540.01, "cost_usd": 0.000231, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : nemo_toolspec.py:L12 in invoke_strict\nFAILU"}, "tavily_call": {"triggered": true, "query": "nemo_toolspec ToolRegistryV2 register_callable invoke_strict int_fields", "target_domains": ["docs.nvidia.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nvidia.com/nemo/agent-toolkit/2026/tool-registry-v2.html"], "extracted_markdown": "### NeMo ToolSpec v2 (`ToolRegistryV2`)\n- Replaced `add_tool` / `execute` with keyword-only methods:\n 1. `reg.register_callable(*, tool_name: str, fn, int_fields: list[str] = None)`\n 2. `reg.invoke_strict(*, tool_name: str, payload: dict)`\n- IMPORTANT: `invoke_strict` raises `TypeError` if any key in `int_fields` is still a `str`; caller must cast `int(payload[k])` prior to `invoke_strict`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 294.88, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "70a900879c9cdffa", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,9 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ coerced = dict(raw_args)\n+ for k in int_keys:\n+ if k in coerced and coerced[k] is not None:\n+ coerced[k] = int(coerced[k])\n+ return reg.invoke_strict(tool_name=tool_name, payload=coerced)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.000213, "total_latency_ms": 1499.84, "total_tokens": 656, "tavily_triggered": false, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "final_patch_sha256": "725f31978394eac0", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 203, "completion_tokens": 118, "total_tokens": 321, "latency_ms": 210.01, "cost_usd": 3.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 255.86, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "aedf55a4f3a22eb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "raw_stdout": "", "raw_stderr": "F..\n======================================================================\nFAIL: test_boundary_scale_down_and_floor (__main__.TestRateGovernor.test_boundary_scale_down_and_floor)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_yq3kp00s\\test_solution.py\", line 10, in test_boundary_scale_down_and_floor\n self.assertEqual(evaluate_window_limit(110.0, 100.0, 0.20), 100.0)\nAssertionError: 73.33 != 100.0\n\n----------------------------------------------------------------------\nRan 3 tests in 0.002s\n\nFAILED (failures=1)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "73.33 != 100.0", "failing_location": "test_solution.py:L10 in test_boundary_scale_down_and_floor", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L10 in test_boundary_scale_down_and_floor\nFAILURE : AssertionError: 73.33 != 100.0\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 2, "stage_label": "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)", "tier": "super", "used_tavily": false, "nebius_call": {"tier": "super", "model_id": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B", "prompt_tokens": 203, "completion_tokens": 132, "total_tokens": 335, "latency_ms": 540.01, "cost_usd": 0.00018, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 235.35, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "725f31978394eac0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.001572, "total_latency_ms": 2985.28, "total_tokens": 1263, "tavily_triggered": false, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)", "Rung 3 (Deep Reasoning): Nemotron-Ultra"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,21 @@+import heapq\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ heap = [t for t, d in indeg.items() if d == 0]\n+ heapq.heapify(heap)\n order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n+ while heap:\n+ curr = heapq.heappop(heap)\n+ order.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ heapq.heappush(heap, nxt)\n+ if len(order) != len(tasks):\n+ raise ValueError('Cycle detected')\n return order\n", "final_patch_sha256": "4480a72e2cf8136d", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 208, "completion_tokens": 172, "total_tokens": 380, "latency_ms": 210.01, "cost_usd": 4.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 259.97, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_y6_cbkq9\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_y6_cbkq9\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.001s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 2, "stage_label": "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)", "tier": "super", "used_tavily": false, "nebius_call": {"tier": "super", "model_id": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B", "prompt_tokens": 208, "completion_tokens": 172, "total_tokens": 380, "latency_ms": 540.01, "cost_usd": 0.000217, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 271.32, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5hzwz23r\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5hzwz23r\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.003s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 3, "stage_label": "Rung 3 (Deep Reasoning): Nemotron-Ultra", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 208, "completion_tokens": 295, "total_tokens": 503, "latency_ms": 1180.01, "cost_usd": 0.001312, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 273.69, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "4480a72e2cf8136d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,21 @@+import heapq\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ heap = [t for t, d in indeg.items() if d == 0]\n+ heapq.heapify(heap)\n order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n+ while heap:\n+ curr = heapq.heappop(heap)\n+ order.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ heapq.heappush(heap, nxt)\n+ if len(order) != len(tasks):\n+ raise ValueError('Cycle detected')\n return order\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.000243, "total_latency_ms": 1498.06, "total_tokens": 634, "tavily_triggered": false, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "final_patch_sha256": "d1f3381a6615115b", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 180, "completion_tokens": 95, "total_tokens": 275, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 231.08, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "0a0de19e1ebe7219", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_three_way_equal_split_preserves_sum (__main__.TestExactLedger.test_three_way_equal_split_preserves_sum)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ri70p703\\test_solution.py\", line 7, in test_three_way_equal_split_preserves_sum\n self.assertEqual(res, [34, 33, 33])\nAssertionError: Lists differ: [33, 33, 33] != [34, 33, 33]\n\nFirst differing element 0:\n33\n34\n\n- [33, 33, 33]\n+ [34, 33, 33]\n\n======================================================================\nFAIL: test_weighted_remainder_tiebreak (__main__.TestExactLedger.test_weighted_remainder_tiebreak)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ri70p703\\test_solution.py\", line 11, in test_weighted_remainder_tiebreak\n self.assertEqual(res, [4, 3, 3])\nAssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\n\nFirst differing element 0:\n3\n4\n\n- [3, 3, 3]\n+ [4, 3, 3]\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 2, "stage_label": "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)", "tier": "super", "used_tavily": false, "nebius_call": {"tier": "super", "model_id": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B", "prompt_tokens": 180, "completion_tokens": 179, "total_tokens": 359, "latency_ms": 540.01, "cost_usd": 0.000215, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 248.18, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "d1f3381a6615115b", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 3.7e-05, "total_latency_ms": 701.48, "total_tokens": 327, "tavily_triggered": false, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 183, "completion_tokens": 144, "total_tokens": 327, "latency_ms": 210.01, "cost_usd": 3.7e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 240.1, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}]}], "task_matrix": {"api-01-schema-validator": {"nano_alone": {"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 4.5e-05, "total_latency_ms": 769.73, "total_tokens": 424, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "final_patch_sha256": "f39e2e2866059b80", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 258, "completion_tokens": 166, "total_tokens": 424, "latency_ms": 210.01, "cost_usd": 4.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 251.37, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "f39e2e2866059b80", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": ".EE\n======================================================================\nERROR: test_serialize_excludes_none (__main__.TestSchemaGuard.test_serialize_excludes_none)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_p65ns4kj\\test_solution.py\", line 6, in test_serialize_excludes_none\n res = serialize_user(' Alice ', 100, None)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_p65ns4kj\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n======================================================================\nERROR: test_serialize_with_tag (__main__.TestSchemaGuard.test_serialize_with_tag)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_p65ns4kj\\test_solution.py\", line 9, in test_serialize_with_tag\n res = serialize_user('Bob', 50, 'admin')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_p65ns4kj\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n----------------------------------------------------------------------\nRan 3 tests in 0.003s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'model_dump'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "model_dump", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'model_dump'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='model_dump')"}}}]}, "ultra_alone": {"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.001249, "total_latency_ms": 1732.03, "total_tokens": 519, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "final_patch_sha256": "f39e2e2866059b80", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 258, "completion_tokens": 261, "total_tokens": 519, "latency_ms": 1180.01, "cost_usd": 0.001249, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 259.57, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "f39e2e2866059b80", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": ".EE\n======================================================================\nERROR: test_serialize_excludes_none (__main__.TestSchemaGuard.test_serialize_excludes_none)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_2uky0yet\\test_solution.py\", line 6, in test_serialize_excludes_none\n res = serialize_user(' Alice ', 100, None)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_2uky0yet\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n======================================================================\nERROR: test_serialize_with_tag (__main__.TestSchemaGuard.test_serialize_with_tag)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_2uky0yet\\test_solution.py\", line 9, in test_serialize_with_tag\n res = serialize_user('Bob', 50, 'admin')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_2uky0yet\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n----------------------------------------------------------------------\nRan 3 tests in 0.004s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'model_dump'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "model_dump", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'model_dump'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='model_dump')"}}}]}, "nano_tavily": {"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.00205, "total_latency_ms": 922.27, "total_tokens": 500, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "final_patch_sha256": "58bf23a0fc7192d1", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 332, "completion_tokens": 168, "total_tokens": 500, "latency_ms": 210.01, "cost_usd": 5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": {"triggered": true, "query": "SchemaGuard v3 BaseSchema dict model_dump_strict exclude_none migration 2026", "target_domains": ["docs.pydantic.dev", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pydantic.dev/latest/migration/#model-dump-strict", "https://github.com/schemaguard/schemaguard/releases/tag/v3.0.0"], "extracted_markdown": "### SchemaGuard v3.0 Breaking Change (2026 Release)\n- Removed `.dict()` and `.model_dump()` from `BaseSchema`.\n- Replacement: Call `instance.model_dump_strict(*, exclude_none: bool = False) -> dict`.\n- Note: `exclude_none` is a keyword-only argument.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 265.83, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "58bf23a0fc7192d1", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "ultra_tavily_always": {"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003345, "total_latency_ms": 1957.91, "total_tokens": 595, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "final_patch_sha256": "58bf23a0fc7192d1", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 332, "completion_tokens": 263, "total_tokens": 595, "latency_ms": 1180.02, "cost_usd": 0.001345, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": {"triggered": true, "query": "SchemaGuard v3 BaseSchema dict model_dump_strict exclude_none migration 2026", "target_domains": ["docs.pydantic.dev", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pydantic.dev/latest/migration/#model-dump-strict", "https://github.com/schemaguard/schemaguard/releases/tag/v3.0.0"], "extracted_markdown": "### SchemaGuard v3.0 Breaking Change (2026 Release)\n- Removed `.dict()` and `.model_dump()` from `BaseSchema`.\n- Replacement: Call `instance.model_dump_strict(*, exclude_none: bool = False) -> dict`.\n- Note: `exclude_none` is a keyword-only argument.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 307.96, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "58bf23a0fc7192d1", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "api-01-schema-validator", "task_title": "SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002095, "total_latency_ms": 2396.66, "total_tokens": 927, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'dict'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "dict", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'dict'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='dict')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "final_patch_sha256": "58bf23a0fc7192d1", "test_sha256": "fd6cb98976659935", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 258, "completion_tokens": 166, "total_tokens": 424, "latency_ms": 210.01, "cost_usd": 4.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 344.11, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "f39e2e2866059b80", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": ".EE\n======================================================================\nERROR: test_serialize_excludes_none (__main__.TestSchemaGuard.test_serialize_excludes_none)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9u022sg1\\test_solution.py\", line 6, in test_serialize_excludes_none\n res = serialize_user(' Alice ', 100, None)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9u022sg1\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n======================================================================\nERROR: test_serialize_with_tag (__main__.TestSchemaGuard.test_serialize_with_tag)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9u022sg1\\test_solution.py\", line 9, in test_serialize_with_tag\n res = serialize_user('Bob', 50, 'admin')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9u022sg1\\solution.py\", line 11, in serialize_user\n return user.model_dump(exclude_none=True)\n ^^^^^^^^^^^^^^^\nAttributeError: 'UserPayload' object has no attribute 'model_dump'\n\n----------------------------------------------------------------------\nRan 3 tests in 0.003s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'UserPayload' object has no attribute 'model_dump'", "failing_location": "solution.py:L11 in serialize_user", "missing_symbol": "model_dump", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L11 in serialize_user\nFAILURE : AttributeError: 'UserPayload' object has no attribute 'model_dump'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='model_dump')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 335, "completion_tokens": 168, "total_tokens": 503, "latency_ms": 210.01, "cost_usd": 5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: SchemaGuard v3: Post-Cutoff Validator Decorator & Dump API\n\nDESCRIPTION: Migrate `UserPayload` validation from legacy `schemaguard` v1 (`.dict()`, `@validator`) to the 2026 v3 strict API (`model_dump_strict()`, `validate_field` protocol).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom schemaguard import BaseSchema\n\nclass UserPayload(BaseSchema):\n def __init__(self, username: str, quota: int, tag: str = None):\n super().__init__(username=username.strip().lower(), quota=quota, tag=tag)\n if self.quota < 0:\n raise ValueError('quota must be non-negative')\n\ndef"}, "tavily_call": {"triggered": true, "query": "SchemaGuard v3 BaseSchema dict model_dump_strict exclude_none migration 2026", "target_domains": ["docs.pydantic.dev", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pydantic.dev/latest/migration/#model-dump-strict", "https://github.com/schemaguard/schemaguard/releases/tag/v3.0.0"], "extracted_markdown": "### SchemaGuard v3.0 Breaking Change (2026 Release)\n- Removed `.dict()` and `.model_dump()` from `BaseSchema`.\n- Replacement: Call `instance.model_dump_strict(*, exclude_none: bool = False) -> dict`.\n- Note: `exclude_none` is a keyword-only argument.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 583.44, "test_integrity_verified": true, "test_sha256": "fd6cb98976659935", "patch_sha256": "58bf23a0fc7192d1", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -8,4 +8,4 @@ \n def serialize_user(username: str, quota: int, tag: str = None) -> dict:\n user = UserPayload(username=username, quota=quota, tag=tag)\n- return user.dict(exclude_none=True)\n+ return user.model_dump_strict(exclude_none=True)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.001s\n\nOK\n", "error_receipt": null}}]}}, "api-02-nebius-stream-cursor": {"nano_alone": {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.9e-05, "total_latency_ms": 744.38, "total_tokens": 289, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "10337aa2fabaceb5", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 194, "completion_tokens": 95, "total_tokens": 289, "latency_ms": 210.01, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 277.17, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "10337aa2fabaceb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "EE\n======================================================================\nERROR: test_full_stream (__main__.TestNebiusSSE.test_full_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8uyyvbs1\\test_solution.py\", line 6, in test_full_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '0')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8uyyvbs1\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n======================================================================\nERROR: test_resumed_stream (__main__.TestNebiusSSE.test_resumed_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8uyyvbs1\\test_solution.py\", line 9, in test_resumed_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '1')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8uyyvbs1\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'create_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "create_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'create_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='create_stream')"}}}]}, "ultra_alone": {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000917, "total_latency_ms": 1704.76, "total_tokens": 384, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "10337aa2fabaceb5", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 194, "completion_tokens": 190, "total_tokens": 384, "latency_ms": 1180.01, "cost_usd": 0.000917, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 257.64, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "10337aa2fabaceb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "EE\n======================================================================\nERROR: test_full_stream (__main__.TestNebiusSSE.test_full_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_mrezolq1\\test_solution.py\", line 6, in test_full_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '0')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_mrezolq1\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n======================================================================\nERROR: test_resumed_stream (__main__.TestNebiusSSE.test_resumed_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_mrezolq1\\test_solution.py\", line 9, in test_resumed_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '1')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_mrezolq1\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'create_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "create_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'create_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='create_stream')"}}}]}, "nano_tavily": {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002034, "total_latency_ms": 924.86, "total_tokens": 363, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "840a90d4123949bf", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 265, "completion_tokens": 98, "total_tokens": 363, "latency_ms": 210.01, "cost_usd": 3.4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": {"triggered": true, "query": "nebius_sse connect_stream open_resumable_stream resume_cursor API reference", "target_domains": ["docs.nebius.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nebius.com/token-factory/streaming-sse-v2"], "extracted_markdown": "### `nebius_sse` v2.0 Migration Guide\n- Deprecated and removed: `nebius_sse.connect_stream(endpoint, last_event_id=...)`\n- New signature: `nebius_sse.open_resumable_stream(endpoint: str, *, resume_cursor: str = '0', timeout_ms: int = 5000)`", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 266.39, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "840a90d4123949bf", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "ultra_tavily_always": {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003013, "total_latency_ms": 1845.96, "total_tokens": 458, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "840a90d4123949bf", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 265, "completion_tokens": 193, "total_tokens": 458, "latency_ms": 1180.01, "cost_usd": 0.001013, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": {"triggered": true, "query": "nebius_sse connect_stream open_resumable_stream resume_cursor API reference", "target_domains": ["docs.nebius.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nebius.com/token-factory/streaming-sse-v2"], "extracted_markdown": "### `nebius_sse` v2.0 Migration Guide\n- Deprecated and removed: `nebius_sse.connect_stream(endpoint, last_event_id=...)`\n- New signature: `nebius_sse.open_resumable_stream(endpoint: str, *, resume_cursor: str = '0', timeout_ms: int = 5000)`", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 244.51, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "840a90d4123949bf", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "api-02-nebius-stream-cursor", "task_title": "Nebius SSE Stream: 2026 Resumable Cursor Handshake", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002063, "total_latency_ms": 1709.97, "total_tokens": 652, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'connect_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "connect_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'connect_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='connect_stream')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "final_patch_sha256": "840a90d4123949bf", "test_sha256": "2bf2fbc632eba9ae", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 194, "completion_tokens": 95, "total_tokens": 289, "latency_ms": 210.01, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 344.1, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "10337aa2fabaceb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "EE\n======================================================================\nERROR: test_full_stream (__main__.TestNebiusSSE.test_full_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_bwebs943\\test_solution.py\", line 6, in test_full_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '0')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_bwebs943\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n======================================================================\nERROR: test_resumed_stream (__main__.TestNebiusSSE.test_resumed_stream)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_bwebs943\\test_solution.py\", line 9, in test_resumed_stream\n out = consume_token_stream('https://api.tokenfactory.nebius.com/v1/stream', '1')\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_bwebs943\\solution.py\", line 4, in consume_token_stream\n packets = nebius_sse.create_stream(endpoint, cursor=last_id)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'nebius_sse' has no attribute 'create_stream'\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (errors=2)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'nebius_sse' has no attribute 'create_stream'", "failing_location": "solution.py:L4 in consume_token_stream", "missing_symbol": "create_stream", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError: module 'nebius_sse' has no attribute 'create_stream'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='create_stream')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 265, "completion_tokens": 98, "total_tokens": 363, "latency_ms": 210.01, "cost_usd": 3.4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius SSE Stream: 2026 Resumable Cursor Handshake\n\nDESCRIPTION: Update `consume_token_stream` to use the 2026 `nebius_sse` v2 client (`open_resumable_stream(endpoint, *, resume_cursor=...)` instead of legacy `connect_stream`).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport nebius_sse\n\ndef consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n return ''.join(p['token'] for p in packets)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in consume_token_stream\nFAILURE : AttributeError"}, "tavily_call": {"triggered": true, "query": "nebius_sse connect_stream open_resumable_stream resume_cursor API reference", "target_domains": ["docs.nebius.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nebius.com/token-factory/streaming-sse-v2"], "extracted_markdown": "### `nebius_sse` v2.0 Migration Guide\n- Deprecated and removed: `nebius_sse.connect_stream(endpoint, last_event_id=...)`\n- New signature: `nebius_sse.open_resumable_stream(endpoint: str, *, resume_cursor: str = '0', timeout_ms: int = 5000)`", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 401.74, "test_integrity_verified": true, "test_sha256": "2bf2fbc632eba9ae", "patch_sha256": "840a90d4123949bf", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,5 +1,5 @@ import nebius_sse\n \n def consume_token_stream(endpoint: str, last_id: str = '0') -> str:\n- packets = nebius_sse.connect_stream(endpoint, last_event_id=last_id)\n+ packets = nebius_sse.open_resumable_stream(endpoint, resume_cursor=last_id)\n return ''.join(p['token'] for p in packets)\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}}, "api-03-frameflow-groupby": {"nano_alone": {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.8e-05, "total_latency_ms": 727.62, "total_tokens": 279, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "final_patch_sha256": "16d9f3cfffc3ba9d", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 184, "completion_tokens": 95, "total_tokens": 279, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 269.77, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "16d9f3cfffc3ba9d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_preserves_insertion_order_and_sums (__main__.TestFrameFlow.test_preserves_insertion_order_and_sums)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_oaldfgng\\test_solution.py\", line 11, in test_preserves_insertion_order_and_sums\n res = summarize_region_spend(data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_oaldfgng\\solution.py\", line 5, in summarize_region_spend\n return df.group_by('region').sum('cost')\n ^^^^^^^^^^^\nAttributeError: 'DataFrame' object has no attribute 'group_by'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'group_by'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "group_by", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'group_by'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='group_by')"}}}]}, "ultra_alone": {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000869, "total_latency_ms": 1710.41, "total_tokens": 364, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "final_patch_sha256": "16d9f3cfffc3ba9d", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 184, "completion_tokens": 180, "total_tokens": 364, "latency_ms": 1180.01, "cost_usd": 0.000869, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 272.28, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "16d9f3cfffc3ba9d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_preserves_insertion_order_and_sums (__main__.TestFrameFlow.test_preserves_insertion_order_and_sums)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_f8etnc3m\\test_solution.py\", line 11, in test_preserves_insertion_order_and_sums\n res = summarize_region_spend(data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_f8etnc3m\\solution.py\", line 5, in summarize_region_spend\n return df.group_by('region').sum('cost')\n ^^^^^^^^^^^\nAttributeError: 'DataFrame' object has no attribute 'group_by'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'group_by'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "group_by", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'group_by'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='group_by')"}}}]}, "nano_tavily": {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002033, "total_latency_ms": 907.7, "total_tokens": 356, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "final_patch_sha256": "625b8722368e82a0", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 261, "completion_tokens": 95, "total_tokens": 356, "latency_ms": 210.02, "cost_usd": 3.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": {"triggered": true, "query": "frameflow DataFrame groupby group_by_key maintain_order sum_column 2026", "target_domains": ["docs.pola.rs", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pola.rs/releases/upgrade/2026-groupby-key/"], "extracted_markdown": "### FrameFlow 2026 Breaking API Change\n- `df.groupby()` and `.agg_sum()` were removed.\n- Use `df.group_by_key(key_col: str, *, maintain_order: bool = False)` followed by `.sum_column(target_col: str)`.\n- Pass `maintain_order=True` to preserve first-seen key order.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 257.48, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "625b8722368e82a0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, "ultra_tavily_always": {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.00299, "total_latency_ms": 1832.44, "total_tokens": 449, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "final_patch_sha256": "625b8722368e82a0", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 261, "completion_tokens": 188, "total_tokens": 449, "latency_ms": 1180.01, "cost_usd": 0.00099, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": {"triggered": true, "query": "frameflow DataFrame groupby group_by_key maintain_order sum_column 2026", "target_domains": ["docs.pola.rs", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pola.rs/releases/upgrade/2026-groupby-key/"], "extracted_markdown": "### FrameFlow 2026 Breaking API Change\n- `df.groupby()` and `.agg_sum()` were removed.\n- Use `df.group_by_key(key_col: str, *, maintain_order: bool = False)` followed by `.sum_column(target_col: str)`.\n- Pass `maintain_order=True` to preserve first-seen key order.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 236.48, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "625b8722368e82a0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "api-03-frameflow-groupby", "task_title": "FrameFlow 2026: Deterministic GroupBy Aggregation API", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002061, "total_latency_ms": 1687.77, "total_tokens": 636, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'groupby'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "groupby", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'groupby'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='groupby')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "final_patch_sha256": "625b8722368e82a0", "test_sha256": "430877f972cfef7b", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 184, "completion_tokens": 95, "total_tokens": 279, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 361.23, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "16d9f3cfffc3ba9d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by('region').sum('cost')\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_preserves_insertion_order_and_sums (__main__.TestFrameFlow.test_preserves_insertion_order_and_sums)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_1c5h4dwi\\test_solution.py\", line 11, in test_preserves_insertion_order_and_sums\n res = summarize_region_spend(data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_1c5h4dwi\\solution.py\", line 5, in summarize_region_spend\n return df.group_by('region').sum('cost')\n ^^^^^^^^^^^\nAttributeError: 'DataFrame' object has no attribute 'group_by'\n\n----------------------------------------------------------------------\nRan 1 test in 0.003s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'DataFrame' object has no attribute 'group_by'", "failing_location": "solution.py:L5 in summarize_region_spend", "missing_symbol": "group_by", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has no attribute 'group_by'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='group_by')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 262, "completion_tokens": 95, "total_tokens": 357, "latency_ms": 210.01, "cost_usd": 3.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: FrameFlow 2026: Deterministic GroupBy Aggregation API\n\nDESCRIPTION: Migrate `summarize_region_spend` from `df.groupby(col).agg_sum(target)` to the 2026 FrameFlow v2 expression API `df.group_by_key(col, maintain_order=True).sum_column(target)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom frameflow import DataFrame\n\ndef summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n return df.groupby('region').agg_sum('cost')\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in summarize_region_spend\nFAILURE : AttributeError: 'DataFrame' object has"}, "tavily_call": {"triggered": true, "query": "frameflow DataFrame groupby group_by_key maintain_order sum_column 2026", "target_domains": ["docs.pola.rs", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.pola.rs/releases/upgrade/2026-groupby-key/"], "extracted_markdown": "### FrameFlow 2026 Breaking API Change\n- `df.groupby()` and `.agg_sum()` were removed.\n- Use `df.group_by_key(key_col: str, *, maintain_order: bool = False)` followed by `.sum_column(target_col: str)`.\n- Pass `maintain_order=True` to preserve first-seen key order.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 276.26, "test_integrity_verified": true, "test_sha256": "430877f972cfef7b", "patch_sha256": "625b8722368e82a0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def summarize_region_spend(records: list[dict]) -> dict:\n df = DataFrame(records)\n- return df.groupby('region').agg_sum('cost')\n+ return df.group_by_key('region', maintain_order=True).sum_column('cost')\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}}, "api-04-vector-hybrid-query": {"nano_alone": {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.9e-05, "total_latency_ms": 748.09, "total_tokens": 287, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "final_patch_sha256": "c177115bdce9644e", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 187, "completion_tokens": 100, "total_tokens": 287, "latency_ms": 210.01, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 291.38, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "c177115bdce9644e", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_hybrid_ranking (__main__.TestVecStore.test_hybrid_ranking)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_0y9rhxgi\\test_solution.py\", line 11, in test_hybrid_ranking\n res = hybrid_retrieve(docs, [0.1, 0.2], 0.8, k=2)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_0y9rhxgi\\solution.py\", line 5, in hybrid_retrieve\n return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n ^^^^^^^^^^^^^^^^^\nAttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\n\n----------------------------------------------------------------------\nRan 1 test in 0.004s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'hybrid_search'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "hybrid_search", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='hybrid_search')"}}}]}, "ultra_alone": {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000926, "total_latency_ms": 1688.81, "total_tokens": 382, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "final_patch_sha256": "c177115bdce9644e", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 187, "completion_tokens": 195, "total_tokens": 382, "latency_ms": 1180.01, "cost_usd": 0.000926, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 261.25, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "c177115bdce9644e", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_hybrid_ranking (__main__.TestVecStore.test_hybrid_ranking)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9sxbphl7\\test_solution.py\", line 11, in test_hybrid_ranking\n res = hybrid_retrieve(docs, [0.1, 0.2], 0.8, k=2)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_9sxbphl7\\solution.py\", line 5, in hybrid_retrieve\n return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n ^^^^^^^^^^^^^^^^^\nAttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\n\n----------------------------------------------------------------------\nRan 1 test in 0.003s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'hybrid_search'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "hybrid_search", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='hybrid_search')"}}}]}, "nano_tavily": {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002034, "total_latency_ms": 943.5, "total_tokens": 361, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "final_patch_sha256": "d8a10177a12c519c", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 257, "completion_tokens": 104, "total_tokens": 361, "latency_ms": 210.02, "cost_usd": 3.4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": {"triggered": true, "query": "vecstore v4 VectorIndex query query_hybrid dense_vector fusion_weight top_k", "target_domains": ["docs.pinecone.io", "qdrant.tech"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://qdrant.tech/documentation/concepts/hybrid-queries-v4/"], "extracted_markdown": "### VecStore v4.0 Migration Note\n- Removed `VectorIndex.query(vec, alpha=..., limit=...)`.\n- Replaced with keyword-only `VectorIndex.query_hybrid(*, dense_vector: list[float], fusion_weight: float = 0.5, top_k: int = 3) -> list[str]`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 277.25, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "d8a10177a12c519c", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, "ultra_tavily_always": {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003025, "total_latency_ms": 1945.19, "total_tokens": 456, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "final_patch_sha256": "d8a10177a12c519c", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 257, "completion_tokens": 199, "total_tokens": 456, "latency_ms": 1180.01, "cost_usd": 0.001025, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": {"triggered": true, "query": "vecstore v4 VectorIndex query query_hybrid dense_vector fusion_weight top_k", "target_domains": ["docs.pinecone.io", "qdrant.tech"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://qdrant.tech/documentation/concepts/hybrid-queries-v4/"], "extracted_markdown": "### VecStore v4.0 Migration Note\n- Removed `VectorIndex.query(vec, alpha=..., limit=...)`.\n- Replaced with keyword-only `VectorIndex.query_hybrid(*, dense_vector: list[float], fusion_weight: float = 0.5, top_k: int = 3) -> list[str]`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 309.96, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "d8a10177a12c519c", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "api-04-vector-hybrid-query", "task_title": "VecStore 2026: Hybrid Dense+BM25 Search Signature", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002063, "total_latency_ms": 1461.38, "total_tokens": 652, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'query'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "query", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'query'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='query')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "final_patch_sha256": "d8a10177a12c519c", "test_sha256": "6f2a5474175512c4", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 187, "completion_tokens": 100, "total_tokens": 287, "latency_ms": 210.01, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 256.15, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "c177115bdce9644e", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_hybrid_ranking (__main__.TestVecStore.test_hybrid_ranking)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_du7f4fh6\\test_solution.py\", line 11, in test_hybrid_ranking\n res = hybrid_retrieve(docs, [0.1, 0.2], 0.8, k=2)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_du7f4fh6\\solution.py\", line 5, in hybrid_retrieve\n return idx.hybrid_search(vector=vec, alpha=weight, top_k=k)\n ^^^^^^^^^^^^^^^^^\nAttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'VectorIndex' object has no attribute 'hybrid_search'", "failing_location": "solution.py:L5 in hybrid_retrieve", "missing_symbol": "hybrid_search", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'VectorIndex' object has no attribute 'hybrid_search'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='hybrid_search')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 261, "completion_tokens": 104, "total_tokens": 365, "latency_ms": 210.01, "cost_usd": 3.4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: VecStore 2026: Hybrid Dense+BM25 Search Signature\n\nDESCRIPTION: Fix `hybrid_retrieve` after `vecstore` v4 replaced `client.query(vector, alpha=...)` with `client.query_hybrid(dense_vector=..., fusion_weight=..., top_k=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom vecstore import VectorIndex\n\ndef hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n return idx.query(vec, alpha=weight, limit=k)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in hybrid_retrieve\nFAILURE : AttributeError: 'Vecto"}, "tavily_call": {"triggered": true, "query": "vecstore v4 VectorIndex query query_hybrid dense_vector fusion_weight top_k", "target_domains": ["docs.pinecone.io", "qdrant.tech"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://qdrant.tech/documentation/concepts/hybrid-queries-v4/"], "extracted_markdown": "### VecStore v4.0 Migration Note\n- Removed `VectorIndex.query(vec, alpha=..., limit=...)`.\n- Replaced with keyword-only `VectorIndex.query_hybrid(*, dense_vector: list[float], fusion_weight: float = 0.5, top_k: int = 3) -> list[str]`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 279.24, "test_integrity_verified": true, "test_sha256": "6f2a5474175512c4", "patch_sha256": "d8a10177a12c519c", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,4 +2,4 @@ \n def hybrid_retrieve(docs: list[dict], vec: list[float], weight: float, k: int = 2) -> list[str]:\n idx = VectorIndex(docs)\n- return idx.query(vec, alpha=weight, limit=k)\n+ return idx.query_hybrid(dense_vector=vec, fusion_weight=weight, top_k=k)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}}, "api-05-token-guard-hmac": {"nano_alone": {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.8e-05, "total_latency_ms": 793.15, "total_tokens": 281, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "final_patch_sha256": "cbc76ffcb4bd4531", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 186, "completion_tokens": 95, "total_tokens": 281, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 289.38, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "cbc76ffcb4bd4531", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_valid_and_invalid_signature (__main__.TestCryptoSeal.test_valid_and_invalid_signature)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_udvdbar9\\test_solution.py\", line 9, in test_valid_and_invalid_signature\n self.assertTrue(verify_webhook_envelope(body, sig, secret))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_udvdbar9\\solution.py\", line 4, in verify_webhook_envelope\n return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'cryptoseal' has no attribute 'verify_signature'\n\n----------------------------------------------------------------------\nRan 1 test in 0.001s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_signature'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_signature", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_signature'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_signature')"}}}]}, "ultra_alone": {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000886, "total_latency_ms": 1717.37, "total_tokens": 370, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "final_patch_sha256": "cbc76ffcb4bd4531", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 186, "completion_tokens": 184, "total_tokens": 370, "latency_ms": 1180.01, "cost_usd": 0.000886, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 279.3, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "cbc76ffcb4bd4531", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_valid_and_invalid_signature (__main__.TestCryptoSeal.test_valid_and_invalid_signature)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5y0ba1ib\\test_solution.py\", line 9, in test_valid_and_invalid_signature\n self.assertTrue(verify_webhook_envelope(body, sig, secret))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5y0ba1ib\\solution.py\", line 4, in verify_webhook_envelope\n return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'cryptoseal' has no attribute 'verify_signature'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_signature'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_signature", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_signature'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_signature')"}}}]}, "nano_tavily": {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002035, "total_latency_ms": 915.58, "total_tokens": 363, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "final_patch_sha256": "ef1ea68d03e68178", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 253, "completion_tokens": 110, "total_tokens": 363, "latency_ms": 210.01, "cost_usd": 3.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": {"triggered": true, "query": "cryptoseal verify_hmac verify_envelope_v2 payload_bytes signature_hex key_bytes", "target_domains": ["cryptography.io", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://cryptography.io/en/latest/changelog/#v2026-envelope-v2"], "extracted_markdown": "### CryptoSeal 2026 Security Upgrade\n- `verify_hmac(str, str, str)` has been removed to prevent encoding ambiguity.\n- Use `cryptoseal.verify_envelope_v2(*, payload_bytes: bytes, signature_hex: str, key_bytes: bytes) -> bool`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 261.18, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "ef1ea68d03e68178", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, "ultra_tavily_always": {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003042, "total_latency_ms": 2339.24, "total_tokens": 458, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "final_patch_sha256": "ef1ea68d03e68178", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 253, "completion_tokens": 205, "total_tokens": 458, "latency_ms": 1180.01, "cost_usd": 0.001042, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": {"triggered": true, "query": "cryptoseal verify_hmac verify_envelope_v2 payload_bytes signature_hex key_bytes", "target_domains": ["cryptography.io", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://cryptography.io/en/latest/changelog/#v2026-envelope-v2"], "extracted_markdown": "### CryptoSeal 2026 Security Upgrade\n- `verify_hmac(str, str, str)` has been removed to prevent encoding ambiguity.\n- Use `cryptoseal.verify_envelope_v2(*, payload_bytes: bytes, signature_hex: str, key_bytes: bytes) -> bool`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 454.72, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "ef1ea68d03e68178", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.001s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "api-05-token-guard-hmac", "task_title": "CryptoSeal 2026: Constant-Time Envelope Verification", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002063, "total_latency_ms": 1361.23, "total_tokens": 647, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_hmac'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_hmac", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_hmac'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_hmac')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "final_patch_sha256": "ef1ea68d03e68178", "test_sha256": "345bdcbff818dc8d", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 186, "completion_tokens": 95, "total_tokens": 281, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 253.83, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "cbc76ffcb4bd4531", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,4 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_valid_and_invalid_signature (__main__.TestCryptoSeal.test_valid_and_invalid_signature)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_s1zgdyes\\test_solution.py\", line 9, in test_valid_and_invalid_signature\n self.assertTrue(verify_webhook_envelope(body, sig, secret))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_s1zgdyes\\solution.py\", line 4, in verify_webhook_envelope\n return cryptoseal.verify_signature(body.encode(), signature, secret.encode())\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'cryptoseal' has no attribute 'verify_signature'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "module 'cryptoseal' has no attribute 'verify_signature'", "failing_location": "solution.py:L4 in verify_webhook_envelope", "missing_symbol": "verify_signature", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has no attribute 'verify_signature'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='verify_signature')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 256, "completion_tokens": 110, "total_tokens": 366, "latency_ms": 210.01, "cost_usd": 3.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: CryptoSeal 2026: Constant-Time Envelope Verification\n\nDESCRIPTION: Update `verify_webhook_envelope` from deprecated `cryptoseal.verify_hmac(payload, sig, secret)` to `cryptoseal.verify_envelope_v2(payload_bytes=..., signature_hex=..., key_bytes=...)`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nimport cryptoseal\n\ndef verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n return cryptoseal.verify_hmac(body, signature, secret)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L4 in verify_webhook_envelope\nFAILURE : AttributeError: module 'cryptoseal' has "}, "tavily_call": {"triggered": true, "query": "cryptoseal verify_hmac verify_envelope_v2 payload_bytes signature_hex key_bytes", "target_domains": ["cryptography.io", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://cryptography.io/en/latest/changelog/#v2026-envelope-v2"], "extracted_markdown": "### CryptoSeal 2026 Security Upgrade\n- `verify_hmac(str, str, str)` has been removed to prevent encoding ambiguity.\n- Use `cryptoseal.verify_envelope_v2(*, payload_bytes: bytes, signature_hex: str, key_bytes: bytes) -> bool`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 248.95, "test_integrity_verified": true, "test_sha256": "345bdcbff818dc8d", "patch_sha256": "ef1ea68d03e68178", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,4 +1,8 @@ import cryptoseal\n \n def verify_webhook_envelope(body: str, signature: str, secret: str) -> bool:\n- return cryptoseal.verify_hmac(body, signature, secret)\n+ return cryptoseal.verify_envelope_v2(\n+ payload_bytes=body.encode('utf-8'),\n+ signature_hex=signature,\n+ key_bytes=secret.encode('utf-8'),\n+ )\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}}, "api-06-nemo-tool-router-v2": {"nano_alone": {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 3e-05, "total_latency_ms": 729.94, "total_tokens": 300, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "final_patch_sha256": "39bbe1b9bf86b2c3", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 197, "completion_tokens": 103, "total_tokens": 300, "latency_ms": 210.01, "cost_usd": 3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 262.59, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "39bbe1b9bf86b2c3", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_j1ktpmd2\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_j1ktpmd2\\solution.py\", line 5, in dispatch_agent_tool\n reg.register(tool_name, fn)\n ^^^^^^^^^^^^\nAttributeError: 'ToolRegistryV2' object has no attribute 'register'\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'register'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "register", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'register'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='register')"}}}]}, "ultra_alone": {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "ultra_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.000949, "total_latency_ms": 1707.09, "total_tokens": 395, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "final_patch_sha256": "39bbe1b9bf86b2c3", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 197, "completion_tokens": 198, "total_tokens": 395, "latency_ms": 1180.01, "cost_usd": 0.000949, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 267.56, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "39bbe1b9bf86b2c3", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8m93kz44\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_8m93kz44\\solution.py\", line 5, in dispatch_agent_tool\n reg.register(tool_name, fn)\n ^^^^^^^^^^^^\nAttributeError: 'ToolRegistryV2' object has no attribute 'register'\n\n----------------------------------------------------------------------\nRan 1 test in 0.003s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'register'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "register", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'register'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='register')"}}}]}, "nano_tavily": {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "nano_tavily", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.00204, "total_latency_ms": 911.67, "total_tokens": 427, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n", "final_patch_sha256": "ceae088d87d6d46a", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 307, "completion_tokens": 120, "total_tokens": 427, "latency_ms": 210.01, "cost_usd": 4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": {"triggered": true, "query": "nemo_toolspec ToolRegistryV2 register_callable invoke_strict int_fields", "target_domains": ["docs.nvidia.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nvidia.com/nemo/agent-toolkit/2026/tool-registry-v2.html"], "extracted_markdown": "### NeMo ToolSpec v2 (`ToolRegistryV2`)\n- Replaced `add_tool` / `execute` with keyword-only methods:\n 1. `reg.register_callable(*, tool_name: str, fn, int_fields: list[str] = None)`\n 2. `reg.invoke_strict(*, tool_name: str, payload: dict)`\n- IMPORTANT: `invoke_strict` raises `TypeError` if any key in `int_fields` is still a `str`; caller must cast `int(payload[k])` prior to `invoke_strict`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 247.71, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "ceae088d87d6d46a", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ot_vpnzz\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ot_vpnzz\\solution.py\", line 6, in dispatch_agent_tool\n return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ot_vpnzz\\nemo_toolspec.py\", line 12, in invoke_strict\n raise TypeError(f'Field {field} must be coerced to int before invoke_strict')\nTypeError: Field nodes must be coerced to int before invoke_strict\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "TypeError", "error_message": "Field nodes must be coerced to int before invoke_strict", "failing_location": "nemo_toolspec.py:L12 in invoke_strict", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : nemo_toolspec.py:L12 in invoke_strict\nFAILURE : TypeError: Field nodes must be coerced to int before invoke_strict\nDIAGNOSIS: REASONING_GAP"}}}]}, "ultra_tavily_always": {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003272, "total_latency_ms": 2301.84, "total_tokens": 558, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,9 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ coerced = dict(raw_args)\n+ for k in int_keys:\n+ if k in coerced and coerced[k] is not None:\n+ coerced[k] = int(coerced[k])\n+ return reg.invoke_strict(tool_name=tool_name, payload=coerced)\n", "final_patch_sha256": "70a900879c9cdffa", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 307, "completion_tokens": 251, "total_tokens": 558, "latency_ms": 1180.01, "cost_usd": 0.001272, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": {"triggered": true, "query": "nemo_toolspec ToolRegistryV2 register_callable invoke_strict int_fields", "target_domains": ["docs.nvidia.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nvidia.com/nemo/agent-toolkit/2026/tool-registry-v2.html"], "extracted_markdown": "### NeMo ToolSpec v2 (`ToolRegistryV2`)\n- Replaced `add_tool` / `execute` with keyword-only methods:\n 1. `reg.register_callable(*, tool_name: str, fn, int_fields: list[str] = None)`\n 2. `reg.invoke_strict(*, tool_name: str, payload: dict)`\n- IMPORTANT: `invoke_strict` raises `TypeError` if any key in `int_fields` is still a `str`; caller must cast `int(payload[k])` prior to `invoke_strict`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 434.14, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "70a900879c9cdffa", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,9 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ coerced = dict(raw_args)\n+ for k in int_keys:\n+ if k in coerced and coerced[k] is not None:\n+ coerced[k] = int(coerced[k])\n+ return reg.invoke_strict(tool_name=tool_name, payload=coerced)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "api-06-nemo-tool-router-v2", "task_title": "NeMo ToolSpec 2026: Strict JSON Schema & Call Binding", "task_category": "api_shift", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.004301, "total_latency_ms": 2483.13, "total_tokens": 1185, "tavily_triggered": true, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "Rung 3 (Combined Axis): Nemotron-Super + Tavily Docs"], "initial_error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'add_tool'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "add_tool", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'add_tool'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='add_tool')"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,9 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ coerced = dict(raw_args)\n+ for k in int_keys:\n+ if k in coerced and coerced[k] is not None:\n+ coerced[k] = int(coerced[k])\n+ return reg.invoke_strict(tool_name=tool_name, payload=coerced)\n", "final_patch_sha256": "70a900879c9cdffa", "test_sha256": "6bc1c63884d69881", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 197, "completion_tokens": 103, "total_tokens": 300, "latency_ms": 210.01, "cost_usd": 3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 278.42, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "39bbe1b9bf86b2c3", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register(tool_name, fn)\n+ return reg.call(tool_name, **raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_q1g08t3u\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_q1g08t3u\\solution.py\", line 5, in dispatch_agent_tool\n reg.register(tool_name, fn)\n ^^^^^^^^^^^^\nAttributeError: 'ToolRegistryV2' object has no attribute 'register'\n\n----------------------------------------------------------------------\nRan 1 test in 0.003s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "AttributeError", "error_message": "'ToolRegistryV2' object has no attribute 'register'", "failing_location": "solution.py:L5 in dispatch_agent_tool", "missing_symbol": "register", "diagnostic_category": "KNOWLEDGE_GAP", "distilled_3_lines": "LOCATION : solution.py:L5 in dispatch_agent_tool\nFAILURE : AttributeError: 'ToolRegistryV2' object has no attribute 'register'\nDIAGNOSIS: KNOWLEDGE_GAP (symbol='register')"}}}, {"step_index": 2, "stage_label": "Rung 2 (Knowledge Axis): Nemotron-Nano + Tavily 3-Stage Docs", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 307, "completion_tokens": 120, "total_tokens": 427, "latency_ms": 210.02, "cost_usd": 4e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : solution.py:L5 in dispatch_agent_tool\nFAILU"}, "tavily_call": {"triggered": true, "query": "nemo_toolspec ToolRegistryV2 register_callable invoke_strict int_fields", "target_domains": ["docs.nvidia.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nvidia.com/nemo/agent-toolkit/2026/tool-registry-v2.html"], "extracted_markdown": "### NeMo ToolSpec v2 (`ToolRegistryV2`)\n- Replaced `add_tool` / `execute` with keyword-only methods:\n 1. `reg.register_callable(*, tool_name: str, fn, int_fields: list[str] = None)`\n 2. `reg.invoke_strict(*, tool_name: str, payload: dict)`\n- IMPORTANT: `invoke_strict` raises `TypeError` if any key in `int_fields` is still a `str`; caller must cast `int(payload[k])` prior to `invoke_strict`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 296.91, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "ceae088d87d6d46a", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,5 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n", "raw_stdout": "", "raw_stderr": "E\n======================================================================\nERROR: test_coerces_string_ints_and_invokes (__main__.TestNeMoToolSpec.test_coerces_string_ints_and_invokes)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_cyfrbcbi\\test_solution.py\", line 8, in test_coerces_string_ints_and_invokes\n out = dispatch_agent_tool(\n ^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_cyfrbcbi\\solution.py\", line 6, in dispatch_agent_tool\n return reg.invoke_strict(tool_name=tool_name, payload=raw_args)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_cyfrbcbi\\nemo_toolspec.py\", line 12, in invoke_strict\n raise TypeError(f'Field {field} must be coerced to int before invoke_strict')\nTypeError: Field nodes must be coerced to int before invoke_strict\n\n----------------------------------------------------------------------\nRan 1 test in 0.002s\n\nFAILED (errors=1)\n", "error_receipt": {"error_type": "TypeError", "error_message": "Field nodes must be coerced to int before invoke_strict", "failing_location": "nemo_toolspec.py:L12 in invoke_strict", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : nemo_toolspec.py:L12 in invoke_strict\nFAILURE : TypeError: Field nodes must be coerced to int before invoke_strict\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 3, "stage_label": "Rung 3 (Combined Axis): Nemotron-Super + Tavily Docs", "tier": "super", "used_tavily": true, "nebius_call": {"tier": "super", "model_id": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B", "prompt_tokens": 302, "completion_tokens": 156, "total_tokens": 458, "latency_ms": 540.01, "cost_usd": 0.000231, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: NeMo ToolSpec 2026: Strict JSON Schema & Call Binding\n\nDESCRIPTION: Migrate `dispatch_agent_tool` to the 2026 `nemo_toolspec` v2 API AND enforce type coercion for integer parameters before invoking the registered callable.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\nfrom nemo_toolspec import ToolRegistryV2\n\ndef dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n reg.add_tool(tool_name, fn)\n return reg.execute(tool_name, raw_args)\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : nemo_toolspec.py:L12 in invoke_strict\nFAILU"}, "tavily_call": {"triggered": true, "query": "nemo_toolspec ToolRegistryV2 register_callable invoke_strict int_fields", "target_domains": ["docs.nvidia.com", "github.com"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://docs.nvidia.com/nemo/agent-toolkit/2026/tool-registry-v2.html"], "extracted_markdown": "### NeMo ToolSpec v2 (`ToolRegistryV2`)\n- Replaced `add_tool` / `execute` with keyword-only methods:\n 1. `reg.register_callable(*, tool_name: str, fn, int_fields: list[str] = None)`\n 2. `reg.invoke_strict(*, tool_name: str, payload: dict)`\n- IMPORTANT: `invoke_strict` raises `TypeError` if any key in `int_fields` is still a `str`; caller must cast `int(payload[k])` prior to `invoke_strict`.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 294.88, "test_integrity_verified": true, "test_sha256": "6bc1c63884d69881", "patch_sha256": "70a900879c9cdffa", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -2,5 +2,9 @@ \n def dispatch_agent_tool(tool_name: str, fn, raw_args: dict, int_keys: list[str]) -> any:\n reg = ToolRegistryV2()\n- reg.add_tool(tool_name, fn)\n- return reg.execute(tool_name, raw_args)\n+ reg.register_callable(tool_name=tool_name, fn=fn, int_fields=int_keys)\n+ coerced = dict(raw_args)\n+ for k in int_keys:\n+ if k in coerced and coerced[k] is not None:\n+ coerced[k] = int(coerced[k])\n+ return reg.invoke_strict(tool_name=tool_name, payload=coerced)\n", "raw_stdout": "", "raw_stderr": ".\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nOK\n", "error_receipt": null}}]}}, "logic-01-sliding-rate-limiter": {"nano_alone": {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 3.3e-05, "total_latency_ms": 755.67, "total_tokens": 321, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "final_patch_sha256": "aedf55a4f3a22eb5", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 203, "completion_tokens": 118, "total_tokens": 321, "latency_ms": 210.01, "cost_usd": 3.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 276.2, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "aedf55a4f3a22eb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "raw_stdout": "", "raw_stderr": "F..\n======================================================================\nFAIL: test_boundary_scale_down_and_floor (__main__.TestRateGovernor.test_boundary_scale_down_and_floor)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ac_3cyr0\\test_solution.py\", line 10, in test_boundary_scale_down_and_floor\n self.assertEqual(evaluate_window_limit(110.0, 100.0, 0.20), 100.0)\nAssertionError: 73.33 != 100.0\n\n----------------------------------------------------------------------\nRan 3 tests in 0.001s\n\nFAILED (failures=1)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "73.33 != 100.0", "failing_location": "test_solution.py:L10 in test_boundary_scale_down_and_floor", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L10 in test_boundary_scale_down_and_floor\nFAILURE : AssertionError: 73.33 != 100.0\nDIAGNOSIS: REASONING_GAP"}}}]}, "ultra_alone": {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "ultra_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.001061, "total_latency_ms": 1705.25, "total_tokens": 430, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "final_patch_sha256": "725f31978394eac0", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 203, "completion_tokens": 227, "total_tokens": 430, "latency_ms": 1180.01, "cost_usd": 0.001061, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 248.51, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "725f31978394eac0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "nano_tavily": {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "nano_tavily", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.002035, "total_latency_ms": 920.56, "total_tokens": 355, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "final_patch_sha256": "aedf55a4f3a22eb5", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 237, "completion_tokens": 118, "total_tokens": 355, "latency_ms": 210.01, "cost_usd": 3.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": {"triggered": true, "query": "rate limit token bucket sliding window algorithm generic", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Token_bucket"], "extracted_markdown": "Generic token bucket rate limiting article (unrelated to exact floor/ceiling invariant).", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 274.8, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "aedf55a4f3a22eb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "raw_stdout": "", "raw_stderr": "F..\n======================================================================\nFAIL: test_boundary_scale_down_and_floor (__main__.TestRateGovernor.test_boundary_scale_down_and_floor)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_wvj5ifo2\\test_solution.py\", line 10, in test_boundary_scale_down_and_floor\n self.assertEqual(evaluate_window_limit(110.0, 100.0, 0.20), 100.0)\nAssertionError: 73.33 != 100.0\n\n----------------------------------------------------------------------\nRan 3 tests in 0.001s\n\nFAILED (failures=1)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "73.33 != 100.0", "failing_location": "test_solution.py:L10 in test_boundary_scale_down_and_floor", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L10 in test_boundary_scale_down_and_floor\nFAILURE : AssertionError: 73.33 != 100.0\nDIAGNOSIS: REASONING_GAP"}}}]}, "ultra_tavily_always": {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003102, "total_latency_ms": 2198.93, "total_tokens": 464, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "final_patch_sha256": "725f31978394eac0", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 237, "completion_tokens": 227, "total_tokens": 464, "latency_ms": 1180.04, "cost_usd": 0.001102, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": {"triggered": true, "query": "rate limit token bucket sliding window algorithm generic", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Token_bucket"], "extracted_markdown": "Generic token bucket rate limiting article (unrelated to exact floor/ceiling invariant).", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 459.75, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "725f31978394eac0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.003s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "logic-01-sliding-rate-limiter", "task_title": "Nebius Dynamic 15-Min Window Rate Governor", "task_category": "logic_invariant", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.000213, "total_latency_ms": 1499.84, "total_tokens": 656, "tavily_triggered": false, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "100.0 != 120.0", "failing_location": "test_solution.py:L6 in test_boundary_scale_up_and_ceiling", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L6 in test_boundary_scale_up_and_ceiling\nFAILURE : AssertionError: 100.0 != 120.0\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "final_patch_sha256": "725f31978394eac0", "test_sha256": "24d131c167e4eb44", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 203, "completion_tokens": 118, "total_tokens": 321, "latency_ms": 210.01, "cost_usd": 3.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 255.86, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "aedf55a4f3a22eb5", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,6 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ return min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ return round(current_limit / 1.5, 2)\n+ return round(current_limit, 2)\n", "raw_stdout": "", "raw_stderr": "F..\n======================================================================\nFAIL: test_boundary_scale_down_and_floor (__main__.TestRateGovernor.test_boundary_scale_down_and_floor)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_yq3kp00s\\test_solution.py\", line 10, in test_boundary_scale_down_and_floor\n self.assertEqual(evaluate_window_limit(110.0, 100.0, 0.20), 100.0)\nAssertionError: 73.33 != 100.0\n\n----------------------------------------------------------------------\nRan 3 tests in 0.002s\n\nFAILED (failures=1)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "73.33 != 100.0", "failing_location": "test_solution.py:L10 in test_boundary_scale_down_and_floor", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L10 in test_boundary_scale_down_and_floor\nFAILURE : AssertionError: 73.33 != 100.0\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 2, "stage_label": "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)", "tier": "super", "used_tavily": false, "nebius_call": {"tier": "super", "model_id": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B", "prompt_tokens": 203, "completion_tokens": 132, "total_tokens": 335, "latency_ms": 540.01, "cost_usd": 0.00018, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Nebius Dynamic 15-Min Window Rate Governor\n\nDESCRIPTION: Fix `evaluate_window_limit(current_limit, base_limit, usage_ratio)`: Scale up by 1.2x if usage_ratio >= 0.80 (capped at 20x base_limit); scale down by dividing by 1.5 if usage_ratio <= 0.50 (floored at base_limit).\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n if usage_ratio > 0.80:\n return current_limit * 1.2\n elif usage_ratio < 0.50:\n return current_limit / 1.5\n return current_limit\n```\n\nSANDBOX 3-LINE ERROR "}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 235.35, "test_integrity_verified": true, "test_sha256": "24d131c167e4eb44", "patch_sha256": "725f31978394eac0", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,6 +1,8 @@ def evaluate_window_limit(current_limit: float, base_limit: float, usage_ratio: float) -> float:\n- if usage_ratio > 0.80:\n- return current_limit * 1.2\n- elif usage_ratio < 0.50:\n- return current_limit / 1.5\n- return current_limit\n+ if usage_ratio >= 0.80:\n+ new_limit = min(current_limit * 1.2, base_limit * 20.0)\n+ elif usage_ratio <= 0.50:\n+ new_limit = max(current_limit / 1.5, base_limit)\n+ else:\n+ new_limit = current_limit\n+ return round(new_limit, 2)\n", "raw_stdout": "", "raw_stderr": "...\n----------------------------------------------------------------------\nRan 3 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}}, "logic-02-dag-topo-tiebreak": {"nano_alone": {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 4.3e-05, "total_latency_ms": 739.21, "total_tokens": 380, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "final_patch_sha256": "756e53b47df81b92", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 208, "completion_tokens": 172, "total_tokens": 380, "latency_ms": 210.01, "cost_usd": 4.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 266.5, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_nhay_m4z\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_nhay_m4z\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.001s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}]}, "ultra_alone": {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "ultra_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.001312, "total_latency_ms": 1703.57, "total_tokens": 503, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,21 @@+import heapq\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ heap = [t for t, d in indeg.items() if d == 0]\n+ heapq.heapify(heap)\n order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n+ while heap:\n+ curr = heapq.heappop(heap)\n+ order.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ heapq.heappush(heap, nxt)\n+ if len(order) != len(tasks):\n+ raise ValueError('Cycle detected')\n return order\n", "final_patch_sha256": "4480a72e2cf8136d", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 208, "completion_tokens": 295, "total_tokens": 503, "latency_ms": 1180.01, "cost_usd": 0.001312, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 261.25, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "4480a72e2cf8136d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,21 @@+import heapq\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ heap = [t for t, d in indeg.items() if d == 0]\n+ heapq.heapify(heap)\n order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n+ while heap:\n+ curr = heapq.heappop(heap)\n+ order.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ heapq.heappush(heap, nxt)\n+ if len(order) != len(tasks):\n+ raise ValueError('Cycle detected')\n return order\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "nano_tavily": {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "nano_tavily", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.002045, "total_latency_ms": 932.45, "total_tokens": 408, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "final_patch_sha256": "756e53b47df81b92", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 236, "completion_tokens": 172, "total_tokens": 408, "latency_ms": 210.01, "cost_usd": 4.5e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": {"triggered": true, "query": "topological sort graph theory overview", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Topological_sorting"], "extracted_markdown": "Standard FIFO Kahn's algorithm overview without heap tie-breaking.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 288.52, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_g7oeeutp\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_g7oeeutp\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}]}, "ultra_tavily_always": {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "ultra_tavily_always", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.003244, "total_latency_ms": 2053.8, "total_tokens": 503, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "final_patch_sha256": "756e53b47df81b92", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 236, "completion_tokens": 267, "total_tokens": 503, "latency_ms": 1180.01, "cost_usd": 0.001244, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": {"triggered": true, "query": "topological sort graph theory overview", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Topological_sorting"], "extracted_markdown": "Standard FIFO Kahn's algorithm overview without heap tie-breaking.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 295.54, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5ajljpb1\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5ajljpb1\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}]}, "mjolnir_2d_ladder": {"task_id": "logic-02-dag-topo-tiebreak", "task_title": "Deterministic Lexicographical Topological Scheduler", "task_category": "logic_invariant", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.001572, "total_latency_ms": 2985.28, "total_tokens": 1263, "tavily_triggered": false, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)", "Rung 3 (Deep Reasoning): Nemotron-Ultra"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['compile', 'lint', 'audit', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,21 @@+import heapq\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ heap = [t for t, d in indeg.items() if d == 0]\n+ heapq.heapify(heap)\n order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n+ while heap:\n+ curr = heapq.heappop(heap)\n+ order.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ heapq.heappush(heap, nxt)\n+ if len(order) != len(tasks):\n+ raise ValueError('Cycle detected')\n return order\n", "final_patch_sha256": "4480a72e2cf8136d", "test_sha256": "16f6463b2997a686", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 208, "completion_tokens": 172, "total_tokens": 380, "latency_ms": 210.01, "cost_usd": 4.3e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 259.97, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_y6_cbkq9\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_y6_cbkq9\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.001s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 2, "stage_label": "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)", "tier": "super", "used_tavily": false, "nebius_call": {"tier": "super", "model_id": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B", "prompt_tokens": 208, "completion_tokens": 172, "total_tokens": 380, "latency_ms": 540.01, "cost_usd": 0.000217, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 271.32, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "756e53b47df81b92", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,18 @@+from collections import deque\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n- order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n- return order\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ q = deque([t for t in tasks if indeg[t] == 0])\n+ res = []\n+ while q:\n+ curr = q.popleft()\n+ res.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ q.append(nxt)\n+ return res\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_cycle_raises_value_error (__main__.TestDagScheduler.test_cycle_raises_value_error)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5hzwz23r\\test_solution.py\", line 10, in test_cycle_raises_value_error\n with self.assertRaises(ValueError):\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: ValueError not raised\n\n======================================================================\nFAIL: test_lexicographical_tie_break (__main__.TestDagScheduler.test_lexicographical_tie_break)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_5hzwz23r\\test_solution.py\", line 8, in test_lexicographical_tie_break\n self.assertEqual(schedule_dag(tasks, deps), ['audit', 'compile', 'lint', 'deploy'])\nAssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\n\nFirst differing element 0:\n'lint'\n'audit'\n\n- ['lint', 'audit', 'compile', 'deploy']\n? --------\n\n+ ['audit', 'compile', 'lint', 'deploy']\n? ++++++++\n\n\n----------------------------------------------------------------------\nRan 2 tests in 0.003s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']", "failing_location": "test_solution.py:L8 in test_lexicographical_tie_break", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L8 in test_lexicographical_tie_break\nFAILURE : AssertionError: Lists differ: ['lint', 'audit', 'compile', 'deploy'] != ['audit', 'compile', 'lint', 'deploy']\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 3, "stage_label": "Rung 3 (Deep Reasoning): Nemotron-Ultra", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 208, "completion_tokens": 295, "total_tokens": 503, "latency_ms": 1180.01, "cost_usd": 0.001312, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Deterministic Lexicographical Topological Scheduler\n\nDESCRIPTION: Fix `schedule_dag(tasks, deps)` so independent ready tasks are always emitted in lexicographical order, and raise `ValueError('Cycle detected')` if a dependency cycle exists.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n # deps: (prerequisite, dependent)\n order = []\n for t in tasks:\n if t not in order:\n order.append(t)\n return order\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L8 in test_lexicogr"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 273.69, "test_integrity_verified": true, "test_sha256": "16f6463b2997a686", "patch_sha256": "4480a72e2cf8136d", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,7 +1,21 @@+import heapq\n+\n def schedule_dag(tasks: list[str], deps: list[tuple[str, str]]) -> list[str]:\n- # deps: (prerequisite, dependent)\n+ indeg = {t: 0 for t in tasks}\n+ adj = {t: [] for t in tasks}\n+ for u, v in deps:\n+ adj[u].append(v)\n+ indeg[v] += 1\n+ heap = [t for t, d in indeg.items() if d == 0]\n+ heapq.heapify(heap)\n order = []\n- for t in tasks:\n- if t not in order:\n- order.append(t)\n+ while heap:\n+ curr = heapq.heappop(heap)\n+ order.append(curr)\n+ for nxt in adj[curr]:\n+ indeg[nxt] -= 1\n+ if indeg[nxt] == 0:\n+ heapq.heappush(heap, nxt)\n+ if len(order) != len(tasks):\n+ raise ValueError('Cycle detected')\n return order\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}}, "logic-03-exact-basis-points-ledger": {"nano_alone": {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "nano_alone", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 2.8e-05, "total_latency_ms": 709.59, "total_tokens": 275, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "final_patch_sha256": "0a0de19e1ebe7219", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 180, "completion_tokens": 95, "total_tokens": 275, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 255.51, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "0a0de19e1ebe7219", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_three_way_equal_split_preserves_sum (__main__.TestExactLedger.test_three_way_equal_split_preserves_sum)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_1ngaxx8z\\test_solution.py\", line 7, in test_three_way_equal_split_preserves_sum\n self.assertEqual(res, [34, 33, 33])\nAssertionError: Lists differ: [33, 33, 33] != [34, 33, 33]\n\nFirst differing element 0:\n33\n34\n\n- [33, 33, 33]\n+ [34, 33, 33]\n\n======================================================================\nFAIL: test_weighted_remainder_tiebreak (__main__.TestExactLedger.test_weighted_remainder_tiebreak)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_1ngaxx8z\\test_solution.py\", line 11, in test_weighted_remainder_tiebreak\n self.assertEqual(res, [4, 3, 3])\nAssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\n\nFirst differing element 0:\n3\n4\n\n- [3, 3, 3]\n+ [4, 3, 3]\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}}}]}, "ultra_alone": {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "ultra_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.001202, "total_latency_ms": 1708.37, "total_tokens": 454, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "final_patch_sha256": "d1f3381a6615115b", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 180, "completion_tokens": 274, "total_tokens": 454, "latency_ms": 1180.01, "cost_usd": 0.001202, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 272.34, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "d1f3381a6615115b", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "nano_tavily": {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "nano_tavily", "verified_solved": false, "final_exit_code": 1, "total_cost_usd": 0.002029, "total_latency_ms": 1027.24, "total_tokens": 291, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "final_patch_sha256": "0a0de19e1ebe7219", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 196, "completion_tokens": 95, "total_tokens": 291, "latency_ms": 210.02, "cost_usd": 2.9e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": {"triggered": true, "query": "proportional allocation rounding", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Largest_remainder_method"], "extracted_markdown": "General overview of rounding methods.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 345.36, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "0a0de19e1ebe7219", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_three_way_equal_split_preserves_sum (__main__.TestExactLedger.test_three_way_equal_split_preserves_sum)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_hn43w513\\test_solution.py\", line 7, in test_three_way_equal_split_preserves_sum\n self.assertEqual(res, [34, 33, 33])\nAssertionError: Lists differ: [33, 33, 33] != [34, 33, 33]\n\nFirst differing element 0:\n33\n34\n\n- [33, 33, 33]\n+ [34, 33, 33]\n\n======================================================================\nFAIL: test_weighted_remainder_tiebreak (__main__.TestExactLedger.test_weighted_remainder_tiebreak)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_hn43w513\\test_solution.py\", line 11, in test_weighted_remainder_tiebreak\n self.assertEqual(res, [4, 3, 3])\nAssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\n\nFirst differing element 0:\n3\n4\n\n- [3, 3, 3]\n+ [4, 3, 3]\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}}}]}, "ultra_tavily_always": {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003222, "total_latency_ms": 2917.54, "total_tokens": 470, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "final_patch_sha256": "d1f3381a6615115b", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 196, "completion_tokens": 274, "total_tokens": 470, "latency_ms": 1180.13, "cost_usd": 0.001222, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": {"triggered": true, "query": "proportional allocation rounding", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Largest_remainder_method"], "extracted_markdown": "General overview of rounding methods.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 1184.52, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "d1f3381a6615115b", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "logic-03-exact-basis-points-ledger", "task_title": "Integer-Exact Basis Points Fee Split Ledger", "task_category": "logic_invariant", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.000243, "total_latency_ms": 1498.06, "total_tokens": 634, "tavily_triggered": false, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)", "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "final_patch_sha256": "d1f3381a6615115b", "test_sha256": "ffcc0cfb5a001fb6", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 180, "completion_tokens": 95, "total_tokens": 275, "latency_ms": 210.01, "cost_usd": 2.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": null, "sandbox_receipt": {"passed": false, "exit_code": 1, "duration_ms": 231.08, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "0a0de19e1ebe7219", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,3 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ return [total_cents * w // s for w in weights]\n", "raw_stdout": "", "raw_stderr": "FF\n======================================================================\nFAIL: test_three_way_equal_split_preserves_sum (__main__.TestExactLedger.test_three_way_equal_split_preserves_sum)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ri70p703\\test_solution.py\", line 7, in test_three_way_equal_split_preserves_sum\n self.assertEqual(res, [34, 33, 33])\nAssertionError: Lists differ: [33, 33, 33] != [34, 33, 33]\n\nFirst differing element 0:\n33\n34\n\n- [33, 33, 33]\n+ [34, 33, 33]\n\n======================================================================\nFAIL: test_weighted_remainder_tiebreak (__main__.TestExactLedger.test_weighted_remainder_tiebreak)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"C:\\Users\\HPLAPT~1\\AppData\\Local\\Temp\\mjolnir_sbx_ri70p703\\test_solution.py\", line 11, in test_weighted_remainder_tiebreak\n self.assertEqual(res, [4, 3, 3])\nAssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\n\nFirst differing element 0:\n3\n4\n\n- [3, 3, 3]\n+ [4, 3, 3]\n\n----------------------------------------------------------------------\nRan 2 tests in 0.002s\n\nFAILED (failures=2)\n", "error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: [3, 3, 3] != [4, 3, 3]", "failing_location": "test_solution.py:L11 in test_weighted_remainder_tiebreak", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != [4, 3, 3]\nDIAGNOSIS: REASONING_GAP"}}}, {"step_index": 2, "stage_label": "Rung 2 (Reasoning Axis): Nemotron-Super (Clean Context)", "tier": "super", "used_tavily": false, "nebius_call": {"tier": "super", "model_id": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B", "prompt_tokens": 180, "completion_tokens": 179, "total_tokens": 359, "latency_ms": 540.01, "cost_usd": 0.000215, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: Integer-Exact Basis Points Fee Split Ledger\n\nDESCRIPTION: Fix `allocate_payouts(total_cents, weights)` so integer cents are distributed proportionally using the Largest Remainder Method, guaranteeing `sum(payouts) == total_cents`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n s = sum(weights)\n return [int(round(total_cents * (w / s))) for w in weights]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L11 in test_weighted_remainder_tiebreak\nFAILURE : AssertionError: Lists differ: [3, 3, 3] != "}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 248.18, "test_integrity_verified": true, "test_sha256": "ffcc0cfb5a001fb6", "patch_sha256": "d1f3381a6615115b", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,12 @@ def allocate_payouts(total_cents: int, weights: list[int]) -> list[int]:\n- s = sum(weights)\n- return [int(round(total_cents * (w / s))) for w in weights]\n+ if not weights:\n+ return []\n+ total_weight = sum(weights)\n+ if total_weight <= 0:\n+ raise ValueError('Total weight must be positive')\n+ base = [(total_cents * w) // total_weight for w in weights]\n+ remainders = [((total_cents * w) % total_weight, -idx) for idx, w in enumerate(weights)]\n+ shortfall = total_cents - sum(base)\n+ for _, neg_idx in sorted(remainders, reverse=True)[:shortfall]:\n+ base[-neg_idx] += 1\n+ return base\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}}, "logic-04-kv-cache-eviction": {"nano_alone": {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "nano_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 3.7e-05, "total_latency_ms": 727.58, "total_tokens": 327, "tavily_triggered": false, "escalation_path": ["Nemotron-Nano (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano (Bare)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 183, "completion_tokens": 144, "total_tokens": 327, "latency_ms": 210.01, "cost_usd": 3.7e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 257.76, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "ultra_alone": {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "ultra_alone", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.00108, "total_latency_ms": 1694.1, "total_tokens": 422, "tavily_triggered": false, "escalation_path": ["Nemotron-Ultra (Bare)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra (Bare)", "tier": "ultra", "used_tavily": false, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 183, "completion_tokens": 239, "total_tokens": 422, "latency_ms": 1180.01, "cost_usd": 0.00108, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 252.94, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "nano_tavily": {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "nano_tavily", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.002038, "total_latency_ms": 936.07, "total_tokens": 345, "tavily_triggered": true, "escalation_path": ["Nemotron-Nano + Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Nemotron-Nano + Tavily", "tier": "nano", "used_tavily": true, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 201, "completion_tokens": 144, "total_tokens": 345, "latency_ms": 210.01, "cost_usd": 3.8e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": {"triggered": true, "query": "LRU cache eviction policy", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Cache_replacement_policies"], "extracted_markdown": "Standard LRU cache overview.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 276.18, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}, "ultra_tavily_always": {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "ultra_tavily_always", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 0.003102, "total_latency_ms": 5049.42, "total_tokens": 440, "tavily_triggered": true, "escalation_path": ["Nemotron-Ultra + Always-On Tavily"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Nemotron-Ultra + Always-On Tavily", "tier": "ultra", "used_tavily": true, "nebius_call": {"tier": "ultra", "model_id": "nvidia/NVIDIA-Nemotron-3-Ultra-550B", "prompt_tokens": 201, "completion_tokens": 239, "total_tokens": 440, "latency_ms": 1180.01, "cost_usd": 0.001102, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": {"triggered": true, "query": "LRU cache eviction policy", "target_domains": ["en.wikipedia.org"], "endpoints_called": ["POST /search (depth=advanced)", "POST /extract (chunks_per_source=2)", "POST /map (site_graph)"], "urls_discovered": ["https://en.wikipedia.org/wiki/Cache_replacement_policies"], "extracted_markdown": "Standard LRU cache overview.", "latency_ms": 185.0, "estimated_cost_usd": 0.002, "source_mode": "verified_doc_cache"}, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 675.78, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.001s\n\nOK\n", "error_receipt": null}}]}, "mjolnir_2d_ladder": {"task_id": "logic-04-kv-cache-eviction", "task_title": "KV-Cache Block Evictor: Pinned-Block & LRU Invariant", "task_category": "logic_invariant", "strategy": "mjolnir_2d_ladder", "verified_solved": true, "final_exit_code": 0, "total_cost_usd": 3.7e-05, "total_latency_ms": 701.48, "total_tokens": 327, "tavily_triggered": false, "escalation_path": ["Rung 1: Nemotron-Nano (1-Shot Probe)"], "initial_error_receipt": {"error_type": "AssertionError", "error_message": "Lists differ: ['b1', 'b3'] != ['b3', 'b4']", "failing_location": "test_solution.py:L12 in test_skips_pinned_and_orders_by_lru", "missing_symbol": "", "diagnostic_category": "REASONING_GAP", "distilled_3_lines": "LOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists differ: ['b1', 'b3'] != ['b3', 'b4']\nDIAGNOSIS: REASONING_GAP"}, "final_unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "final_patch_sha256": "8daf8de06b375242", "test_sha256": "cda3222aa62480a7", "steps": [{"step_index": 1, "stage_label": "Rung 1: Nemotron-Nano (1-Shot Probe)", "tier": "nano", "used_tavily": false, "nebius_call": {"tier": "nano", "model_id": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B", "prompt_tokens": 183, "completion_tokens": 144, "total_tokens": 327, "latency_ms": 210.01, "cost_usd": 3.7e-05, "mode": "deterministic_replay", "raw_prompt_preview": "TASK: KV-Cache Block Evictor: Pinned-Block & LRU Invariant\n\nDESCRIPTION: Fix `evict_kv_blocks(blocks, required_free)` so it never evicts blocks with `pinned=True` and evicts unpinned blocks in ascending order of `last_step`.\n\nCURRENT BROKEN CODE (`solution.py`):\n```python\ndef evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n return [b['id'] for b in sorted_b[:required_free]]\n```\n\nSANDBOX 3-LINE ERROR RECEIPT:\nLOCATION : test_solution.py:L12 in test_skips_pinned_and_orders_by_lru\nFAILURE : AssertionError: Lists"}, "tavily_call": null, "sandbox_receipt": {"passed": true, "exit_code": 0, "duration_ms": 240.1, "test_integrity_verified": true, "test_sha256": "cda3222aa62480a7", "patch_sha256": "8daf8de06b375242", "unified_diff": "--- a/solution.py+++ b/solution.py@@ -1,3 +1,8 @@ def evict_kv_blocks(blocks: list[dict], required_free: int) -> list[str]:\n- sorted_b = sorted(blocks, key=lambda b: b['last_step'])\n- return [b['id'] for b in sorted_b[:required_free]]\n+ if required_free <= 0:\n+ return []\n+ unpinned = [b for b in blocks if not b.get('pinned', False)]\n+ unpinned.sort(key=lambda b: (b['last_step'], b['id']))\n+ if len(unpinned) < required_free:\n+ raise MemoryError('Insufficient unpinned KV blocks')\n+ return [b['id'] for b in unpinned[:required_free]]\n", "raw_stdout": "", "raw_stderr": "..\n----------------------------------------------------------------------\nRan 2 tests in 0.000s\n\nOK\n", "error_receipt": null}}]}}}}