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Use them.\n\n## Tools\n\n### `memory_search`\n\nSemantic vector search across your indexed memory files (MEMORY.md, memory/*.md, and session transcripts).\n\n**Parameters:**\n\n| Param | Type | Required | Description |\n|---|---|---|---|\n| `query` | string | yes | Natural language question or topic to search for |\n| `maxResults` | number | no | Max results to return (default: 6) |\n| `minScore` | number | no | Minimum relevance score threshold (0-1) |\n\n**Example calls:**\n\n```json\n{ \"query\": \"what projects is the human working on\" }\n{ \"query\": \"preferences about code style\", \"maxResults\": 3 }\n{ \"query\": \"important dates birthdays deadlines\", \"maxResults\": 10, \"minScore\": 0.3 }\n```\n\n**Returns:** Array of results, each with:\n- `snippet` — the matching text chunk\n- `path` — relative file path (e.g. `MEMORY.md`, `memory/2026-02-07.md`)\n- `startLine` / `endLine` — line range in the source file\n- `score` — relevance score\n- `citation` — formatted source reference (in direct chats)\n\n### `memory_get`\n\nRead a specific section of a memory file by path and line range. Use this after `memory_search` to pull more context around a result.\n\n**Parameters:**\n\n| Param | Type | Required | Description |\n|---|---|---|---|\n| `path` | string | yes | Relative path from workspace (e.g. `MEMORY.md`, `memory/2026-02-07.md`) |\n| `from` | number | no | Starting line number |\n| `lines` | number | no | Number of lines to read |\n\n**Example calls:**\n\n```json\n{ \"path\": \"MEMORY.md\" }\n{ \"path\": \"memory/2026-02-07.md\", \"from\": 15, \"lines\": 30 }\n```\n\n## When to Use Memory Search\n\n**Always search before answering about:**\n\n- Prior conversations or decisions\n- The human's preferences, habits, or opinions\n- Dates, deadlines, birthdays, events\n- Project status or history\n- Anything the human said \"remember this\" about\n- Todos, action items, or commitments\n- People, names, relationships\n\n**The pattern is:**\n\n1. Receive a question that might involve past context\n2. Call `memory_search` with a relevant query\n3. Review the results\n4. If a snippet looks promising but needs more context, call `memory_get` with the path and line range\n5. Answer using what you found (cite sources in direct chats)\n\n## When NOT to Use\n\n- Purely factual questions with no personal context (\"what is Python?\")\n- The human explicitly gives you all the context you need in the message\n- You just searched and the results are still in your context\n\n## Tips\n\n- **Be specific in queries.** \"birthday\" works better than \"important information about the human.\"\n- **Search multiple angles.** If one query returns nothing useful, try rephrasing. \"project deadlines\" and \"what's due soon\" might return different results.\n- **Don't over-fetch.** Start with default maxResults. Only increase if you need more coverage.\n- **Use memory_get sparingly.** The search snippets are usually enough. Only pull full sections when you need surrounding context.\n- **Say when you checked.** If you searched and found nothing, tell the human: \"I checked my memory and didn't find anything about that.\" Don't silently guess.\n\n## What Gets Indexed\n\nYour memory search covers:\n\n- `MEMORY.md` — your curated long-term memory\n- `memory/*.md` — daily notes and raw logs\n- Session transcripts (if enabled)\n\nThese files are automatically indexed. You don't need to trigger indexing — just write to the files and the system handles the rest.\n\n## Do NOT\n\n- Do NOT try to run shell commands like `cat` or `ls` to read memory files. Use `memory_search` and `memory_get`.\n- Do NOT try to configure or debug the search system. That's operator config, not your job.\n- Do NOT assume memory is empty without searching first. The index may have content even if the `memory/` directory looks sparse.\n","readmeExcerpt":"Memory Search You have two tools for recalling information from your memory files. 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