Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
- Updated skill.
What This Skill Does
Graph-native memory engine for AI agents that stores memories as local JSON files by default, with no Docker, cloud API, or external database required. Supports hybrid vector and keyword search, biological decay, Zettelkasten-style graph linking, and trust-gated conflict resolution. Install via npm and run immediately.
Unlike cloud-hosted alternatives like Mem0, it stores data locally by default and adds memory decay, graph linking, conflict quarantine, and an explainability API without requiring any infrastructure.
When to use it
- Persisting agent findings across sessions after context compaction
- Detecting contradictory facts before storing updated configuration values
- Sharing a memory graph across multiple agents working on the same codebase
- Automatically fading stale security findings or outdated deployment notes over time
- Grouping memories from a deployment sprint into a named episode for later retrieval
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: remember that the API gateway has an XSS vulnerability and search for related security findings
- 1Call mem.store('agent', 'XSS vulnerability in API gateway login form', { category: 'finding', importance: 0.9 }) to persist the finding
- 2Memory engine computes keyword tokens and links the new entry to semantically similar existing memories via the graph index
- 3Call mem.search('agent', 'security vulnerabilities') to retrieve related findings
- 4Results are returned with trust, confidence, provenance, and optional explain metadata
Ranked list of security-related memories with similarity scores, provenance sources, and graph links to connected entries