memory-searchSearch and retrieve relevant information from your indexed memory files using semantic queries and direct file reads for context.
Install via ClawdBot CLI:
clawdbot install aigentic-net/memory-searchYou have two tools for recalling information from your memory files. Use them.
memory_searchSemantic vector search across your indexed memory files (MEMORY.md, memory/*.md, and session transcripts).
Parameters:
| Param | Type | Required | Description |
|---|---|---|---|
| query | string | yes | Natural language question or topic to search for |
| maxResults | number | no | Max results to return (default: 6) |
| minScore | number | no | Minimum relevance score threshold (0-1) |
Example calls:
{ "query": "what projects is the human working on" }
{ "query": "preferences about code style", "maxResults": 3 }
{ "query": "important dates birthdays deadlines", "maxResults": 10, "minScore": 0.3 }
Returns: Array of results, each with:
snippet — the matching text chunkpath — relative file path (e.g. MEMORY.md, memory/2026-02-07.md)startLine / endLine — line range in the source filescore — relevance scorecitation — formatted source reference (in direct chats)memory_getRead a specific section of a memory file by path and line range. Use this after memory_search to pull more context around a result.
Parameters:
| Param | Type | Required | Description |
|---|---|---|---|
| path | string | yes | Relative path from workspace (e.g. MEMORY.md, memory/2026-02-07.md) |
| from | number | no | Starting line number |
| lines | number | no | Number of lines to read |
Example calls:
{ "path": "MEMORY.md" }
{ "path": "memory/2026-02-07.md", "from": 15, "lines": 30 }
Always search before answering about:
The pattern is:
memory_search with a relevant querymemory_get with the path and line rangeYour memory search covers:
MEMORY.md — your curated long-term memorymemory/*.md — daily notes and raw logsThese files are automatically indexed. You don't need to trigger indexing — just write to the files and the system handles the rest.
cat or ls to read memory files. Use memory_search and memory_get.memory/ directory looks sparse.Generated Mar 1, 2026
An AI support agent uses memory search to recall previous customer interactions and preferences, enabling personalized responses and issue resolution without asking repetitive questions. It searches for past tickets, user feedback, and product history to provide consistent and informed support.
An AI assistant leverages memory search to remember user schedules, preferences, and important dates like birthdays or deadlines, helping manage daily tasks and reminders efficiently. It queries memory for past conversations and notes to anticipate needs and offer proactive suggestions.
An AI consultant uses memory search to track project statuses, team decisions, and action items from past meetings, ensuring continuity and informed recommendations. It retrieves historical data and commitments to avoid duplication and align with ongoing workflows.
An AI system in healthcare employs memory search to recall patient history, treatment plans, and appointment logs, aiding in personalized care coordination and compliance tracking. It accesses indexed notes and transcripts to support clinical decisions without manual data lookup.
An AI assistant in legal settings uses memory search to find prior case references, client preferences, and deadline information from stored documents, streamlining research and case preparation. It ensures accurate citation and context retrieval for legal professionals.
Offer the memory search skill as part of a subscription-based AI platform for businesses, charging monthly fees per user or usage tier. This model provides recurring revenue and scalability, with updates and support included to attract enterprises and teams.
Provide basic memory search functionality for free to individual users, with advanced features like higher result limits or custom indexing available in paid tiers. This model drives user adoption and upsells, targeting both casual users and professional clients.
Sell customized memory search packages to large organizations with specific integration needs, such as enhanced security or compliance features. This model involves one-time or annual licensing fees, focusing on high-value contracts and dedicated support.
💬 Integration Tip
Integrate memory search by embedding it into existing AI workflows, ensuring seamless query handling and result display without disrupting user experience. Test with sample data to optimize query specificity and relevance thresholds.
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