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/crabpot-perf-metrics

@e0b7247
by Vincent Kocvincentkoc/dotskills108 stars
9

Interpret Crabpot and OpenClaw performance dashboard metrics, import-loop profiles, runtime profiles, and branch-to-branch perf deltas without over-reading noisy samples.

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Use this Skill: https://skilld.dev/gh/vincentkoc/dotskills/crabpot-perf-metrics

This session only. Nothing lands on disk.

SKILL.md

≈48 tokens always: the name and description. ≈1.1k when used: this file. ≈105 more on demand in 1 file.

Purpose

Turn Crabpot/OpenClaw perf artifacts into a clear read: what changed, what is real signal, what is stale/noisy, and what action is worth taking.

When to use

  • Comparing openclaw/crabpot branches such as main, crab-beta, or crab-development.
  • Reading reports/crabpot-dashboard-data.json, reports/crabpot-import-loop-profile.json, reports/crabpot-runtime-profile.json, README dashboard metrics, or GitHub Actions report artifacts.
  • The user asks about perf, runtime, CPU, RSS, import loop, OpenClaw import/activate, dashboard deltas, or whether a Crabpot performance change is meaningful.

Inputs

  • Target repo or local checkout, usually openclaw/crabpot.
  • Branches, refs, PRs, or artifact URLs to compare.
  • Optional target OpenClaw labels/SHAs if the comparison crosses openclaw@latest, beta, or openclaw/openclaw@main.

Workflow

  1. Establish freshness before interpreting numbers.
    • Resolve branch heads and report timestamps.
    • Compare dashboard JSON with raw profile JSON on the same branch.
    • If one branch is stale, say so first and avoid strong conclusions.
    • Prefer raw JSON over README snippets when they disagree.
  2. Separate the metric families.
    • import-loop-profile: cheap cold capture loop against a tiny fixture. Good for harness/import drift, weak for production runtime claims.
    • runtime-profile: macro command timings across Crabpot analysis commands. Better trend signal for real suite cost.
    • OpenClaw lifecycle: import plus activate phases. If openClawLifecycleCount is 0, the branch dashboard does not include this signal.
  3. Interpret import-loop metrics conservatively.
    • Use p50WallMs, p95WallMs, p50PluginWallDeltaMs, p95PluginWallDeltaMs, maxPluginPeakRssDeltaMb, and maxPluginCpuDeltaMsEstimate.
    • Treat 3-run p95 as "worst of three", not a stable tail latency estimate.
    • A small wall-time bump with flat plugin RSS/CPU usually means jitter or module-resolution overhead, not a memory/CPU regression.
    • Baseline-adjusted plugin deltas are more useful than raw wall/RSS/CPU values.
  4. Interpret runtime profile metrics as the stronger trend.
    • Use summary.p50WallMs, summary.p95WallMs, summary.maxPeakRssMb, summary.maxCpuMsEstimate, and summary.maxHarnessHeapDeltaMb.
    • Inspect per-command medians for the source of change: fixture-inspection, compat-report-registry, contract-capture, synthetic-probe-plan, cold-import-readiness, workspace-plan, platform-probes, and import-loop-profile.
    • Broadly uniform slowdowns across target-aware commands usually point at target OpenClaw surface parsing or registry work, not one plugin fixture.
    • If RSS is flat and CPU moves only slightly, call it a wall-clock/runtime overhead change, not a memory leak.
  5. Account for surface changes.
    • Different fixture counts, entrypoint counts, OpenClaw labels, or commit SHAs make the comparison partly apples-to-oranges.
    • New fixtures can raise issue/probe counts while leaving perf healthy.
    • OpenClaw main vs npm latest can improve compatibility while adding modest analysis overhead.
  6. Give the user a direct read.
    • Start with the conclusion.
    • Prefer bullets and a short summary over tables unless the user asks for a table.
    • Include exact deltas and classify them: real regression, modest slowdown, noise, stale data, or missing signal.
    • Recommend one next action: refresh dashboard, add a dedicated lifecycle lane, investigate a specific command, or ignore as noise.

Useful Commands

Use gh if ghx is unavailable.

Fetch current branch artifacts from GitHub:

gh api /repos/openclaw/crabpot/contents/reports/crabpot-dashboard-data.json?ref=crab-development

Prefer a small Node or jq extraction over manual README scraping. Pull these files when available:

  • reports/crabpot-dashboard-data.json
  • reports/crabpot-import-loop-profile.json
  • reports/crabpot-runtime-profile.json
  • reports/crabpot-ci-summary.json

Outputs

  • Concise perf summary in bullets.
  • Freshness caveats when needed.
  • Important deltas with interpretation.
  • Clear owner/action recommendation, especially when lifecycle import+activate is missing from dashboard artifacts.

Source: SKILL.md on GitHub

Third-party checks

1 warning17d3 checks · Risk SAFE
  • Gen Agent Trust Hub17d

    The skill is safe to use. It provides instructions for interpreting performance metrics and dashboard data for the Crabpot and OpenClaw projects. It suggests using standard GitHub CLI commands to fetch public performance reports for analysis and does not contain any malicious patterns or dangerous commands.

  • Socket17d

    No alerts

  • Snyk17d

    Risk: MEDIUM · 1 issue

Provenance

Signed by skilld at e0b7247. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last week.

Activeupdated 2 weeks ago

Capability

Other metadata
metadata
{
  "workflow-exemption": "Read-only metric interpretation checklist; freshness and uncertainty are reported with the result.",
  "source": "https://github.com/vincentkoc/dotskills"
}

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