SkillPulse

Profile offline OpenClaw skill run samples to detect latency, CPU, and memory bottlenecks and compare sessions.

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.