Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Analyzes git commit patterns to monitor autonomous agent operational health. Measures commit frequency, category distribution, and idle gaps to classify operational state as healthy, warning, or critical. Built from patterns observed during a real autonomous operation period.
Commit history is a passive, zero-overhead signal that captures operational state without requiring dedicated logging infrastructure or external monitoring setup.
When to use it
- Check if an autonomous agent is stuck or idle
- Identify peak productive hours across a workweek
- Monitor task category balance between learning and execution
- Detect extended idle gaps that signal blockers
- Generate daily or weekly commit health reports
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Is my agent operating normally right now?
- 1Runs analyzer.sh health against the last 24 hours of commits
- 2Calculates commits per hour and compares to the 3-6/hr healthy threshold
- 3Checks Learning commit ratio against the 30% minimum
- 4Finds the largest idle gap between consecutive commits
- 5Outputs status label (healthy/warning/critical) with a specific recommendation
Health report showing 42 commits at 1.75/hr, WARNING status, 4h 23m idle gap detected, recommendation to check queue for blockers