skill-profiler

# Skill Profiler Analyze offline sample sets and surface the slowest or heaviest skills before they become production regressions. ## When to use - You have JSON sample logs with `latencyMs`, `cpuMs`, and `memoryMb`. - You want threshold-based hotspot detection for local review or CI. - You need a shareable JSON or HTML report, or a before/after comparison between two runs. ## Commands ```bash node {baseDir}/bin/skill-profiler.js run --input ./samples.json node {baseDir}/bin/skill-profiler.js report --input ./samples.json --out ./report.html node {baseDir}/bin/skill-profiler.js compare --left ./v1.json --right ./v2.json ``` ## Sample input ```json [ { "sessionId": "s1", "skill": "clawshield", "latencyMs": 1320, "cpuMs": 910, "memoryMb": 240 } ] ``` ## What it reports - Average latency and p95 latency per skill - Average CPU and peak memory per skill - Bottlenecks using configurable latency, CPU, and memory thresholds - Session diffs showing added, removed, and changed skills ## Boundaries - Skill Profiler is built for offline sample analysis, not live tracing. - It depends on the quality of the input samples and does not capture traces by itself.