Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Initial public release - transforms passive memory into active AI development through asynchronous reflection, structured memory extraction, question generation, and identity evolution.
What This Skill Does
Runs post-session reflection to extract structured memories categorized by type (fact, preference, commitment, relationship, etc.) and assigned confidence scores. Generates follow-up questions from each session and stores them for the next conversation. When the user returns, surfaces relevant questions for a contextually aware session start.
Unlike passive note-taking or raw session logs, it actively integrates memories and generates questions, so the next session opens with genuine continuity rather than performed familiarity.
When to use it
- Resuming a long-running project after days away without losing context
- Tracking commitments an agent made across multiple sessions
- Surfacing unresolved questions at the start of a new conversation
- Maintaining a persistent self-model for an AI agent over time
- Auditing what preferences or facts were learned in prior sessions
Example Workflow
Here's how your AI assistant might use this skill in practice.
User returns after a 2-day break on an ongoing agent infrastructure project
- 1Heartbeat triggers `continuity reflect` after session idle exceeds threshold
- 2Analyzes the previous conversation and extracts typed memories with confidence scores
- 3Generates follow-up questions for unresolved threads and stores them to questions.md
- 4Updates identity.md with any growth or narrative changes noted in the session
- 5Runs `continuity greet` at session start to surface the top pending questions
Agent opens with: "Welcome back. A few things from last time: How is the Lovable backend progressing? Has the token launch timing been decided?"