skill-monitor

# 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 skill usage. If no `skill_effectiveness` data exists in metrics: "Metrics were computed before skill tracking was added. Run `/session-scan --rescan` to recompute." **OTel `invocation_trigger` (CC v2.1.126+)**: when `compute-metrics.py` ingests `c...