session_search_memory
Search session history by meaning using vector embeddings to find contextually similar sessions, even when exact wording differs. Use when keyword search returns no results or query phrasing varies.
Instructions
Search session history semantically (by meaning, not just keywords). Uses vector embeddings to find sessions with similar context, even when the exact wording differs. Requires pgvector extension in Supabase.
Complements knowledge_search (keyword-based) — use this when keyword search returns no results or when the query is phrased differently from stored summaries.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum results to return (default: 5, max: 20). | |
| query | Yes | Natural language search query describing what you're looking for. | |
| project | No | Optional: limit search to a specific project. | |
| activation | No | Configuration for ACT-R inspired Spreading Activation. Use this to find structurally related memories beyond direct semantic/keyword hits. | |
| enable_trace | No | If true, returns a separate MEMORY TRACE content block with search strategy, latency breakdown (embedding vs storage), and scoring metadata. Default: false. | |
| context_boost | No | If true, appends current project and working context to the search query before embedding generation, naturally biasing results toward contextually relevant memories. Useful when searching within a specific project context. Default: false. | |
| similarity_threshold | No | Minimum similarity score 0-1 (default: 0.7). Higher = more relevant, fewer results. |