Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Persistent memory plugin for OpenClaw agents that survives session resets and restarts. Uses hybrid SQLite FTS5 keyword search combined with Ollama vector embeddings for semantic recall. Automatically extracts and injects relevant facts around each LLM turn.
Combines keyword and semantic search in a single plugin with zero npm dependencies, so agents get accurate retrieval without a separate vector database or additional packages.
When to use it
- Remembering user preferences across separate agent sessions
- Tracking project decisions without re-explaining context each time
- Detecting when an agent is stuck repeating the same topic
- Looking up all stored facts about a specific entity on demand
- Running long-term agents that accumulate knowledge over days or weeks
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: 'What database did we decide to use for the auth service?'
- 1Extract keywords from the user message
- 2Run FTS5 keyword search against SQLite memory store
- 3Run Ollama vector similarity search if enabled
- 4Merge and deduplicate results from both searches
- 5Inject matching memories as context before sending to LLM
Agent responds with the previously stored decision: 'You decided on PostgreSQL for the auth service on 2025-11-03, preferring it over MySQL for its JSON support.'
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.