| name | mnemon |
| description | Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle. |
mnemon
Workflow
- Remember:
mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent
- Diff is built in: duplicates are skipped, conflicts are auto-replaced.
- Output includes
action (added/updated/skipped), semantic_candidates, and causal_candidates.
- Link (evaluate candidates from step 1 using judgment):
- Review
causal_candidates: link only when the memories are genuinely causally related.
- Review
semantic_candidates: high similarity alone is not enough; skip unrelated keyword matches.
- Syntax:
mnemon link <id> <candidate> --type <causal|semantic> --weight <0-1> [--meta '<json>']
- Recall:
mnemon recall "<query>" --limit 10
Commands
mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent
mnemon link <id1> <id2> --type <type> --weight <0-1> [--meta '<json>']
mnemon recall "<query>" --limit 10
mnemon search "<query>" --limit 10
mnemon import --dry-run <file>
mnemon import <file>
mnemon forget <id>
mnemon related <id> --edge causal
mnemon gc --threshold 0.4
mnemon gc --keep <id>
mnemon status
mnemon log
mnemon store list
mnemon store create <name>
mnemon store set <name>
mnemon store remove <name>
Guardrails
- Use memory only when it can materially improve continuity or task quality.
- Do not store secrets, passwords, tokens, private keys, or short-lived operational noise.
- Categories:
preference, decision, insight, fact, context
- Edge types:
temporal, semantic, causal, entity
- Max 8,000 chars per insight.
