benchmark

Solid

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

AI & Automation 196,640 stars 30253 forks Updated 2 days ago MIT

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Skill Content

# 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:...

Details

Author
affaan-m
Repository
affaan-m/everything-claude-code
Created
4 months ago
Last Updated
2 days ago
Language
JavaScript
License
MIT

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