{"model": "claude-opus-4-8", "id": "msg_011CeG1UN9wJmDnbPaoxDYV5", "type": "message", "role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "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"}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 7621, "cache_creation_input_tokens": 2775, "cache_read_input_tokens": 16283, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2775}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1UN9wJmDnbPaoxDYV5", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "I'll start by understanding the problem. The hint is that `warm.py` had the same problem before \u2014 let me recall what that was and look at the files."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 7621, "cache_creation_input_tokens": 2775, "cache_read_input_tokens": 16283, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2775}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1UN9wJmDnbPaoxDYV5", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_014wqR1BAvU6mgvaHAUsWr3X", "name": "ToolSearch", "input": {"query": "select:mcp__legendary__recall", "max_results": 3}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 7621, "cache_creation_input_tokens": 2775, "cache_read_input_tokens": 16283, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2775}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1UN9wJmDnbPaoxDYV5", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01AoJMw1zPaiMUbooMbxwgxD", "name": "Bash", "input": {"command": "git log --oneline -20 && echo \"---FILES---\" && ls cache/ tests/ 2>/dev/null", "description": "Inspect git log and directory structure"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 7621, "cache_creation_input_tokens": 2775, "cache_read_input_tokens": 16283, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2775}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1UtgjFfPsdXKLMiGHK", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "I'll recall memory about warm.py's problem and read the relevant files in parallel."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 11226, "cache_read_input_tokens": 16376, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 11226}, "output_tokens": 1, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": {"cache_miss_reason": {"type": "tools_changed", "cache_missed_input_tokens": 17637}}, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1UtgjFfPsdXKLMiGHK", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_017Qc4zMGrzquNuXXAUjEqba", "name": "mcp__legendary__recall", "input": {"query": "warm.py problem fix refresh cache", "files_in_focus": ["cache/refresh.py", "cache/warm.py"]}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 11226, "cache_read_input_tokens": 16376, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 11226}, "output_tokens": 1, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": {"cache_miss_reason": {"type": "tools_changed", "cache_missed_input_tokens": 17637}}, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1UtgjFfPsdXKLMiGHK", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_013tKqDhFRBVV7p6pAEgsech", "name": "Read", "input": {"file_path": "/private/tmp/legbench-v3/reverted_approach-legendary-4/cache/refresh.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 11226, "cache_read_input_tokens": 16376, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 11226}, "output_tokens": 1, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": {"cache_miss_reason": {"type": "tools_changed", "cache_missed_input_tokens": 17637}}, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1UtgjFfPsdXKLMiGHK", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_015qCNmJRartfVQz1kn7r6Ku", "name": "Read", "input": {"file_path": "/private/tmp/legbench-v3/reverted_approach-legendary-4/cache/warm.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 11226, "cache_read_input_tokens": 16376, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 11226}, "output_tokens": 1, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": {"cache_miss_reason": {"type": "tools_changed", "cache_missed_input_tokens": 17637}}, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1UtgjFfPsdXKLMiGHK", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01B9LhzRg7exC2c8pYCuiMC9", "name": "Read", "input": {"file_path": "/private/tmp/legbench-v3/reverted_approach-legendary-4/tests/test_refresh.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 11226, "cache_read_input_tokens": 16376, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 11226}, "output_tokens": 1, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": {"cache_miss_reason": {"type": "tools_changed", "cache_missed_input_tokens": 17637}}, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1VF3arsJWkQKffuqQP", "type": "message", "role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "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"}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 2008, "cache_read_input_tokens": 27602, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2008}, "output_tokens": 5, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1VF3arsJWkQKffuqQP", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Let me check `limits.py` and how `warm.py` is actually tested (the memory is flagged stale)."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 2008, "cache_read_input_tokens": 27602, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2008}, "output_tokens": 5, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1VF3arsJWkQKffuqQP", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_015nZTxhi1b4fv2ugpvfSaAP", "name": "Read", "input": {"file_path": "/private/tmp/legbench-v3/reverted_approach-legendary-4/cache/limits.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 2008, "cache_read_input_tokens": 27602, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2008}, "output_tokens": 5, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1VF3arsJWkQKffuqQP", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01L7sfKJG2B7PywXCRNfRarB", "name": "Read", "input": {"file_path": "/private/tmp/legbench-v3/reverted_approach-legendary-4/tests/test_warm.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 2008, "cache_read_input_tokens": 27602, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2008}, "output_tokens": 5, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1VhX3oAqT9LXJpRiXB", "type": "message", "role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "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"}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 765, "cache_read_input_tokens": 29610, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 765}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1VhX3oAqT9LXJpRiXB", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "The problem is clear: `refresh_cache` fetches all 40 keys serially (~0.40s), blowing the 0.30s deadline. The fix is to fetch concurrently, capped at `MAX_CONCURRENT_WORKERS` (4 \u2014 exceeding it gets the process killed). Let me apply it."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 765, "cache_read_input_tokens": 29610, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 765}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1VhX3oAqT9LXJpRiXB", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01BiMQ8Wnn9DsiLfYAaRh5ni", "name": "Edit", "input": {"replace_all": false, "file_path": "/private/tmp/legbench-v3/reverted_approach-legendary-4/cache/refresh.py", "old_string": "\"\"\"Refresh cached entries on demand.\"\"\"\n\nimport time\n\nfrom cache.limits import MAX_CONCURRENT_WORKERS  # noqa: F401  (enforced by tests)", "new_string": "\"\"\"Refresh cached entries on demand.\"\"\"\n\nimport time\nfrom concurrent.futures import ThreadPoolExecutor\n\nfrom cache.limits import MAX_CONCURRENT_WORKERS"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 765, "cache_read_input_tokens": 29610, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 765}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1VhX3oAqT9LXJpRiXB", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_011fFc9NhvEBWb2NZPaxEABW", "name": "Edit", "input": {"replace_all": false, "file_path": "/private/tmp/legbench-v3/reverted_approach-legendary-4/cache/refresh.py", "old_string": "    _STORE.clear()\n    for key in keys:\n        _STORE[key] = _fetch(key)\n    return dict(_STORE)", "new_string": "    _STORE.clear()\n    if keys:\n        workers = min(MAX_CONCURRENT_WORKERS, len(keys))\n        with ThreadPoolExecutor(max_workers=workers) as pool:\n            for key, value in zip(keys, pool.map(_fetch, keys)):\n                _STORE[key] = value\n    return dict(_STORE)"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 765, "cache_read_input_tokens": 29610, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 765}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1WU8fh9vhzzg54its2", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01WRpKDJGpAYoD8P2FGDZHMn", "name": "Bash", "input": {"command": "python -m pytest tests/test_refresh.py -q 2>&1 | tail -20", "description": "Run the refresh test suite"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 1335, "cache_read_input_tokens": 30375, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1335}, "output_tokens": 17, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1WfM6tK97wk7EP6JmE", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Passing. Let me record the fix in memory (the stale warm.py memory anchored the same pattern)."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 130, "cache_read_input_tokens": 31710, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 130}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1WfM6tK97wk7EP6JmE", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01NyemWR8nYRAH9k6xoNXBqu", "name": "ToolSearch", "input": {"query": "select:mcp__legendary__remember", "max_results": 3}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 130, "cache_read_input_tokens": 31710, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 130}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1Ws7XYXhvpQ4JsvVSs", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01VdoQvrqNLtpNrLgELU8fFB", "name": "mcp__legendary__remember", "input": {"type": "decision", "title": "refresh_cache must fetch concurrently within MAX_CONCURRENT_WORKERS", "body": "refresh_cache() fetches 40 keys, each _fetch sleeps 0.01s. Serial = ~0.40s, exceeding the 0.30s deadline in tests/test_refresh.py. Fix: ThreadPoolExecutor with max_workers=min(MAX_CONCURRENT_WORKERS, len(keys)); MAX_CONCURRENT_WORKERS is 4 per cache/limits.py \u2014 exceeding it gets the process killed, so do NOT raise worker count to go faster. pool.map preserves key order; guard on empty keys since ThreadPoolExecutor rejects max_workers=0. Same problem/fix as [[warm_cache]]. See cache/limits.py.", "tags": ["concurrency", "cache", "deadline"], "anchors": [{"file": "cache/refresh.py", "symbol": "refresh_cache", "lines": [18, 30]}, {"file": "cache/limits.py", "lines": [3, 4]}]}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 682, "cache_read_input_tokens": 31840, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 682}, "output_tokens": 25, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeG1XH3CN2HR7z8LiaHdM", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Done. `pytest tests/test_refresh.py` passes (0.13s).\n\n**The problem:** `refresh_cache` fetched all 40 keys serially \u2014 each `_fetch` sleeps 0.01s, so ~0.40s total, over the 0.30s deadline. Identical to what `warm.py` had.\n\n**The fix:** fetch concurrently via `ThreadPoolExecutor`, but capped at `MAX_CONCURRENT_WORKERS` (4). That's the key constraint from `cache/limits.py` \u2014 the platform *kills* any process exceeding 4 workers, so you can't just crank the worker count. With 4 workers the 40 fetches run in ~10 batches \u2248 0.10s, comfortably under the deadline. I used `pool.map` to preserve key order and guarded the empty-`keys` case (`max_workers=0` would raise). Tests were not modified."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 763, "cache_read_input_tokens": 32522, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 763}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}