23 lines
1.1 KiB
Markdown
23 lines
1.1 KiB
Markdown
---
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id: e94ae963-9bf9-4adc-b0d7-ec18d9e70999
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type: decision
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title: "Semantic search enabled by default for memory recall"
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tags: [cognitive-memory, decision, semantic-search, configuration]
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importance: 0.7
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confidence: 0.8
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created: "2026-02-19T22:03:22.589620+00:00"
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updated: "2026-02-19T22:03:22.589620+00:00"
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---
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Changed `recall()` default from `semantic=False` to `semantic=True`. All recall calls now use semantic+keyword merge when embeddings exist.
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**Rationale:** With mtime-based embeddings caching, warm semantic recall takes ~200ms — imperceptible within Claude Code sessions where API roundtrips are measured in seconds. The quality improvement from conceptual matching justifies the small overhead.
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**Changes made:**
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- `client.py`: `recall()` parameter default `semantic=True`
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- `client.py`: CLI flag changed from `--semantic` (opt-in) to `--no-semantic` (opt-out)
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- `mcp_server.py`: `arguments.get("semantic", True)`, updated tool description
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- `SKILL.md`: Updated all examples and documentation
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**Merge weights:** 60% semantic, 40% keyword. Use `semantic=false` / `--no-semantic` when speed matters more than depth (~3ms vs ~200ms).
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