Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
- Initial release of version 1.1.0. - Updated scripts/health_monitor.py. - No user-facing changes to documentation.
What This Skill Does
Monitors deployed skills for performance drift, errors, and unexpected behavior changes. Tracks latency percentiles, error rates, output format changes, and resource usage across invocations. Health data is stored locally per skill with configurable alerting thresholds.
Provides per-skill output drift detection that generic infrastructure monitors miss.
When to use it
- Detecting latency increases after an upstream API update
- Catching error rate spikes in a production agent before users notice
- Identifying output format changes after a model behavior change
- Setting per-skill alert thresholds for automated notifications
- Reviewing 24-hour trends to spot memory or CPU accumulation
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: check the health of my deployed summarizer skill
- 1Runs health check against the summarizer skill command
- 2Records execution latency, error count, and output snapshot
- 3Compares current metrics against configured thresholds
- 4Flags any output drift or threshold violations
Console report showing p50/p95 latency, error rate, and any threshold violations for the summarizer skill