skill-monitor
Analyze skill effectiveness across sessions. Computes per-skill metrics (action rate, friction, outcomes), identifies degrading skills, and generates improvement recommendations. Requires session-scan data in metrics.jsonl.
npx skills add oliver-kriska/claude-elixir-phoenix --skill skill-monitor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Skill Monitor Closed-loop skill effectiveness monitoring. Reads session metrics, computes per-skill signals, identifies what's working and what needs improvement. Inspired by the deploy-monitor-evaluate-improve feedback loop: skills get better over time instead of staying static. ## Requirements Requires `.claude/session-metrics/metrics.jsonl` from `/session-scan`. If no data: suggest running `/session-scan` first. ## Usage ``` /skill-monitor # Dashboard: all skills /skill-monitor --skill review # Deep-dive on one skill /skill-monitor --improve # Generate improvement recommendations /skill-monitor --window 30d # Change comparison window (default: 7d) ``` ## What Main Context Does ### Step 1: Parse Arguments Extract from `$ARGUMENTS`: - **`--skill NAME`**: Focus on one skill (e.g., `review`, `plan`, `investigate`) - **`--improve`**: Spawn analysis agent for improvement recommendations - **`--window PERIOD`**: Comparison window (`7d`, `30d`, `all`; default: `7d`) ### Step 2: Load Metrics Read `.claude/session-metrics/metrics.jsonl`. For each entry, extract the `skill_effectiveness` field (added by compute-metrics.py v2). Filter by window period. Count sessions with and without skil
- Requirements
- Usage
- What Main Context Does
- Step 1: Parse Arguments
- Step 2: Load Metrics
- Step 3: Compute Per-Skill Aggregates
- Step 4: Display Dashboard
- Step 5: Improvement Mode (--improve)
- Step 6: Write Output
- Iron Laws
- Integration
- References
What does the skill-monitor skill do?
Analyze skill effectiveness across sessions. Computes per-skill metrics (action rate, friction, outcomes), identifies degrading skills, and generates improvement recommendations. Requires session-scan data in metrics.jsonl.
How do I install it?
Run `npx skills add oliver-kriska/claude-elixir-phoenix --skill skill-monitor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From oliver-kriska/claude-elixir-phoenix, a repository with 515 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.