Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Runs a rule-based quality check on agent output before it reaches the user. Evaluates clarity, conciseness, actionability, and structure. Returns exit code 0 for approved output or 1 when improvement is needed.
Catches output quality issues without LLM API calls, keeping review costs at zero.
When to use it
- Catching verbose or unclear agent responses before delivery
- Filtering low-quality output in automated agent pipelines
- Running post-generation checks without extra API costs
- Enforcing response structure standards across agent workflows
- Validating output during CI/CD for agent-based tools
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Check this agent response before sending it
- 1Pipe the generated response text to self-review/index.js via stdin
- 2Rule-based engine evaluates clarity, conciseness, actionability, and structure
- 3Returns exit code 0 if output passes all checks
- 4Returns exit code 1 with feedback if output needs improvement
Exit code 0 with approved response, or exit code 1 indicating which checks failed