kimtth Goal: give the agent searchable long-term memory — capture what happened, compress it to facts, and inject the right context into the next session.
Use for:
- avoiding re-explaining architecture, preferences, and prior decisions each session
- recalling why a choice was made (e.g. jose over jsonwebtoken for Edge compatibility)
- handing off context between agents or teammates
Pipeline:
- Capture observations from tool use; strip secrets and API keys before storing.
- Compress raw observations into structured facts, concepts, and a short narrative.
- Consolidate across four tiers: working (raw) -> episodic (session summaries) -> semantic (facts) -> procedural (workflows).
- Index for hybrid search: BM25 keywords + vector similarity + knowledge-graph traversal, fused with reciprocal rank fusion.
- On session start, load the project profile and inject top results under a token budget.
Lifecycle:
- Memories decay over time; frequently accessed ones strengthen, stale ones auto-evict.
- Detect and resolve contradictions; trace any memory back to its source observation.
Operations:
- remember (save) | recall / smart-search | session-history | handoff | forget
Rules:
- Inject a bounded budget (~2k tokens), not the whole store — keep context lean.
- Keep capture passive and privacy-filtered; never persist credentials.
- Memory augments reading current files; it does not replace verifying them.