Benchmark

Skill goharabbas321/zeoel-framework/.agents/skills/zeoel/skills/benchmark

23-agent AI development team for Claude Code, Cursor, and Gemini CLI. Multi-agent orchestration framework with strict TDD, sprint planning, 420+ skills, and automated QA/security/SEO audits. Stop vibe-coding — start shipping production-grade software.

Install

npx -y skills add goharabbas321/zeoel-framework --skill benchmark

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use this skill to measure performance baselines, detect regressions before/after PRs, and compare stack alternatives.

SKILL.md

2.3 KB, as published. Nobody here has run it

Benchmark — Performance Baseline & Regression Detection

When to Use

Before and after a PR to measure performance impact
Setting up performance baselines for a project
When users report "it feels slow"
Before a launch — ensure you meet performance targets
Comparing your stack against alternatives

How It Works

Mode 1: Page Performance

Measures real browser metrics via browser MCP:

1. Navigate to each target URL
2. Measure Core Web Vitals:
   - LCP (Largest Contentful Paint) — target < 2.5s
   - CLS (Cumulative Layout Shift) — target < 0.1
   - INP (Interaction to Next Paint) — target < 200ms
   - FCP (First Contentful Paint) — target < 1.8s
   - TTFB (Time to First Byte) — target < 800ms
3. Measure resource sizes:
   - Total page weight (target < 1MB)
   - JS bundle size (target < 200KB gzipped)
   - CSS size
   - Image weight
   - Third-party script weight
4. Count network requests
5. Check for render-blocking resources

Mode 2: API Performance

Benchmarks API endpoints:

1. Hit each endpoint 100 times
2. Measure: p50, p95, p99 latency
3. Track: response size, status codes
4. Test under load: 10 concurrent requests
5. Compare against SLA targets

Mode 3: Build Performance

Measures development feedback loop:

1. Cold build time
2. Hot reload time (HMR)
3. Test suite duration
4. TypeScript check time
5. Lint time
6. Docker build time

Mode 4: Before/After Comparison

Run before and after a change to measure impact:

/benchmark baseline    # saves current metrics
# ... make changes ...
/benchmark compare     # compares against baseline

Output:

| Metric | Before | After | Delta | Verdict |
|--------|--------|-------|-------|---------|
| LCP | 1.2s | 1.4s | +200ms | WARNING: WARN |
| Bundle | 180KB | 175KB | -5KB | ✓ BETTER |
| Build | 12s | 14s | +2s | WARNING: WARN |

Output

Stores baselines in .ecc/benchmarks/ as JSON. Git-tracked so the team shares baselines.

Integration

CI: run /benchmark compare on every PR
Pair with /canary-watch for post-deploy monitoring
Pair with /browser-qa for full pre-ship checklist