session_search_memory
Search past sessions by semantic meaning using vector embeddings to find relevant context when keyword searches fail or wording differs.
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 |
|---|---|---|---|
| query | Yes | Natural language search query describing what you're looking for. | |
| project | No | Optional: limit search to a specific project. | |
| limit | No | Maximum results to return (default: 5, max: 20). | |
| similarity_threshold | No | Minimum similarity score 0-1 (default: 0.7). Higher = more relevant, fewer results. | |
| 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. | |
| activation | No | Configuration for ACT-R inspired Spreading Activation. Use this to find structurally related memories beyond direct semantic/keyword hits. |