Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Extracts patterns from AI agent session transcripts into a weighted knowledge graph. Repeated insights strengthen over time through Hebbian reinforcement, while unused ones decay. Compiles a token-budgeted summary called the metacognition lens for use in future sessions.
Persists cross-session learning with weighted decay, avoiding the loss of accumulated context that comes with static system prompts or per-session memory alone.
When to use it
- Identifying recurring mistakes an agent makes across sessions
- Tracking user communication preferences over time
- Automatically pruning outdated or weakened beliefs via decay
- Discovering higher-level principles from specific session events
- Running scheduled self-reflection cycles on a cron timer
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: run the metacognition integration cycle
- 1Run `python3 scripts/metacognition.py decay` to prune weak entries
- 2Read recent session transcripts using sessions_list and sessions_history
- 3Analyze conversation for recurring patterns, relationship signals, and confidence mismatches
- 4Add 1-3 principle-level insights with typed categories such as overrides, decisions, or curiosities
- 5Run reweave then compile to rebuild graph connections and regenerate the metacognition lens
Updated metacognition-lens.md with reinforced insights and newly extracted principles, ready for injection into the next session context