OpenClaw Skill Usage Tracker: Monitor Which Skills You Actually Use
A developer has created a tool to track basic usage analytics for OpenClaw skills, addressing the challenge of monitoring which skills are actually being used when they're invoked implicitly through natural language.
Key Features
The tool tracks skill invocation counts and provides usage breakdowns. Example output shows compact data like:
skill: weather (37) - agent: elon 26 | main 10 | tim 1 - channel: disc/el 26 | wa 6 | tim 2 | unknown 3 ===================================== skill: skill-vetter (12) - agent: main 9 | tim 2 | elon 1 - channel: wa 7 | disc/el 3 | tim 1 | unknown 1 ===================================== skill: github (8) - agent: elon 6 | main 1 | unknown 1 - channel: disc/el 6 | wa 1 | unknown 1
Current features include:
- Track skill invocation counts
- Provide top skill rankings by period: 1d / 7d / 30d / all
- Break down where a skill is used by agent and by channel (Discord, Telegram, etc.)
- Join usage across different installations (for example MBP + Mac mini) if you run a distributed OpenClaw server setup
How It Works and Limitations
The current mechanism increments counts when SKILL.md is read, with some deduping to avoid over-counting. Because of this approach, certain backend-style skills are not counted perfectly, especially things like memory-related skills.
In some cases you may see unknown agent or channel if the routing metadata is incomplete.
Availability
The tool is available at https://github.com/lucifinil/openclaw-skill-usage. The developer is seeking feedback from other OpenClaw users or skill authors and is willing to iterate based on suggestions.
📖 Read the full source: r/openclaw
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