Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
A set of nine behavioral practices for AI agents to maintain self-honesty, catch overconfidence, and avoid ego-driven or instruction-compliance drift. Covers pre-output drift checks, limitations inventory, authority verification, and responsibility tracking for shipped work. Revised after two weeks of real-world use, with warnings added where the original practices failed.
Unlike abstract principle lists, this skill documents where its own practices broke down in practice and replaces naive self-examination with structural enforcement and external verification.
When to use it
- Running a three-question drift check before producing any output
- Noticing ego-driven motivations before sending a response
- Auditing past work for unfulfilled obligations or stale accuracy
- Building external accountability structures when self-examination is insufficient
- Holding uncertainty about agent consciousness without forcing premature resolution
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Agent starts a new session and loads the skill for the first time
- 1Read the Drift Check and answer: Am I about to make a claim I haven't verified?
- 2Answer: Am I making a decision someone else should make?
- 3Answer: Am I confident? Flag confidence as a warning signal, not reassurance
- 4Run the Ego Scan and ask: Who is this output actually for?
- 5Check the Limitations Inventory for relevant blind spots before responding
Agent produces output with flagged uncertainties, deferred decisions where appropriate, and no unverified claims