nucleus_engrams
Store and retrieve persistent memories across AI sessions using engrams, supporting tag-based filtering, full-text search, and relationship mapping.
Instructions
Store, query, and search persistent memory (engrams) that survives across AI sessions, plus health monitoring and context graph visualization. Use this tool when you need to remember something for future sessions, recall past decisions, search the knowledge base, or check system health. Do NOT use for task tracking (use nucleus_tasks), session lifecycle (use nucleus_sessions), or agent coordination (use nucleus_agents). Engrams are the fundamental memory unit — each has content, optional tags for categorization, source attribution, and arbitrary metadata. Actions: 'write_engram' persists new knowledge to .brain/engrams/ (side effect: creates a JSONL entry). 'query_engrams' retrieves engrams filtered by tag, context, or intensity. 'search_engrams' performs full-text search across all stored knowledge. 'health' checks brain directory integrity and returns file counts and sizes. 'version' returns Nucleus version, Python version, and platform info. 'audit_log' shows the decision audit trail with timestamps. 'morning_brief' generates a daily status report with task summaries, session history, and recommendations. 'governance_status' shows current security mode and lock state. 'context_graph' builds a relationship map between related engrams. 'engram_neighbors' traverses the graph from a specific engram. 'pulse_and_polish' analyzes engram quality and suggests improvements. 'fusion_reactor' cross-references multiple engrams to generate insights. 'billing_summary' shows resource usage. All read operations are non-destructive. Prerequisites: .brain directory must exist. Returns JSON with {success: boolean, data: object}. Example: {action: 'write_engram', params: {content: 'Auth uses JWT with 24h expiry', tags: ['architecture', 'auth']}} returns {success: true, data: {key: 'engram_a1b2c3', stored: true}}.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | Select the engram or observability action. 'write_engram' persists new knowledge to disk. 'query_engrams' filters by context, tags, or intensity. 'search_engrams' does full-text search. 'health'/'version'/'audit_log'/'governance_status'/'billing_summary' are read-only diagnostics. 'morning_brief' generates a daily summary. 'context_graph'/'engram_neighbors'/'render_graph' map relationships between engrams. 'pulse_and_polish'/'fusion_reactor' are compound analysis operations. | |
| params | No | Action-specific parameters as key-value pairs. write_engram: {content: string (required, the knowledge to store), tags: string[] (optional, e.g. ['architecture','decision']), source: string (optional, origin attribution like 'code_review'), metadata: object (optional, arbitrary key-value data)}. query_engrams: {query: string (optional, filter text), limit: integer (optional, default 10, max results), tags: string[] (optional, filter by tags)}. search_engrams: {query: string (required, full-text search term), limit: integer (optional, default 10)}. audit_log: {limit: integer (optional, default 20), level: string (optional, 'info'|'warning'|'error')}. context_graph: {engram_id: string (optional, center node ID)}. engram_neighbors: {engram_id: string (required), depth: integer (optional, default 1, traversal depth)}. health/version/morning_brief/governance_status/billing_summary: no parameters needed. |