LaunchKit · 2026
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memo-persistent-memory

Persistent memory system - automatic context capture and semantic search.

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by @webdevtodayjason

Setup & Installation

openclaw skills install @webdevtodayjason/memo-persistent-memory

Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:

npx clawhub install memo-persistent-memory

What This Skill Does

Adds persistent memory to OpenClaw sessions using a local SQLite database with full-text search. Memories are captured automatically after each response and injected before the next prompt, keeping context available across sessions.

Unlike in-session context that resets when the conversation ends, this system persists observations to a local database and retrieves only semantically relevant memories, avoiding token bloat.

When to use it

  • Remembering project-specific decisions across multiple work sessions
  • Recalling user preferences without re-explaining them each time
  • Tracking ongoing tasks and their current state between conversations
  • Surfacing relevant past context when starting a new related task
  • Storing and retrieving notes from previous debugging sessions

Example Workflow

Here's how your AI assistant might use this skill in practice.

INPUT

User asks: 'What was the database schema we decided on last week?'

AGENT
  1. 1auto-recall triggers and searches the memory store for relevant observations
  2. 2memory_search queries the SQLite FTS5 index with natural language
  3. 3matching memories are injected into the prompt context before the agent responds
  4. 4agent uses the retrieved schema details to answer directly
OUTPUT

Agent answers with the previously stored schema decision without the user needing to repeat it