engram
Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessions.
What this skill does
# Engram — Agent Memory Local semantic memory with biological decay, typed memories, and relationship graphs. No API keys. No cloud. ## Boot Sequence ```bash engram search "<current task or context>" --limit 10 ``` Always recall before working. Accessed memories get salience-boosted. ## Storing ```bash engram add "Client uses React with TypeScript" --type fact --tags react,client engram add "We decided to pause ads" --type decision --tags ads echo "Raw conversation text" | engram ingest ``` Types: fact, decision, preference, event, relationship ## Searching ```bash engram search "what tech stack" engram search "pricing decisions" --type decision engram search "client status" --agent client-agent ``` ## Relationships ```bash engram relate <src> <tgt> --type supports engram auto-relate <id> engram relations <id> ``` Types: related_to, supports, contradicts, caused_by, supersedes, part_of, references ## Key Concepts - **Decay**: Unused memories lose salience daily. Recalled ones get boosted. - **Types**: Filter by fact, decision, preference, event, relationship. - **Scoping**: global, agent, private, shared. - **Dedup**: >92% similarity auto-merges. ## Quick Reference ```bash engram stats engram recall --limit 10 engram export > backup.json engram import backup.json ```
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