Benchmark

by affaan-mef648e01899ba3e8dc6371642deaaf64b4477775MIT275K starsListed Oct 9, 2026Updated Oct 9, 2026Repository updated 4 days ago

Measure performance baselines and detect regressions across browser Core Web Vitals (LCP, INP, CLS, page weight), API endpoint latency percentiles, and build/test feedback times, with before/after comparison stored in git-tracked .ecc/benchmarks JSON. Use when checking page speed, responding to 'it feels slow' reports, verifying launch performance targets, or comparing stack alternatives.

Instructions onlyData & Analytics

AI-generated overview

Measures web page, API, and build performance baselines and detects regressions by comparing before/after metrics.

What it does: The skill defines four measurement modes: browser Core Web Vitals and page weight, API endpoint latency percentiles under load, build and test feedback times, and before/after comparison. It records baselines as JSON in a git-tracked .ecc/benchmarks directory so a team shares them. Comparison output is a table of metric, before, after, delta, and verdict.
When to use it: Use it before and after a pull request to measure performance impact, when setting up project baselines, when users report that something feels slow, before a launch to check performance targets, or when comparing stack alternatives.
Requirements: Requires a browser MCP for page measurements and a git repository for storing baselines. It ships no scripts; it is instructions only.

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 URL2. 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 < 800ms3. Measure resource sizes:   - Total page weight (target < 1MB)   - JS bundle size (target < 200KB gzipped)   - CSS size   - Image weight   - Third-party script weight4. Count network requests5. Check for render-blocking resources

1. Navigate to each target URL2. 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 < 800ms3. Measure resource sizes:   - Total page weight (target < 1MB)   - JS bundle size (target < 200KB gzipped)   - CSS size   - Image weight   - Third-party script weight4. Count network requests5. Check for render-blocking resources

Mode 2: API Performance

Benchmarks API endpoints:

1. Hit each endpoint 100 times2. Measure: p50, p95, p99 latency3. Track: response size, status codes4. Test under load: 10 concurrent requests5. Compare against SLA targets

1. Hit each endpoint 100 times2. Measure: p50, p95, p99 latency3. Track: response size, status codes4. Test under load: 10 concurrent requests5. Compare against SLA targets

Mode 3: Build Performance

Measures development feedback loop:

1. Cold build time2. Hot reload time (HMR)3. Test suite duration4. TypeScript check time5. Lint time6. Docker build time

1. Cold build time2. Hot reload time (HMR)3. Test suite duration4. TypeScript check time5. Lint time6. 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

/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 |

| 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

Source and attribution

Source:affaan-m/ECCinskills/benchmarkat commitef648e0

License: MIT

Content belongs to its original authors. SourceWeft indexes it from a public repository.

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Benchmark

Benchmark — Performance Baseline & Regression Detection

When to Use

How It Works

Mode 1: Page Performance

Mode 2: API Performance

Mode 3: Build Performance

Mode 4: Before/After Comparison

Output

Integration

Source and attribution

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