Agent skill · data analytics · affaan-m
benchmark
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.
Why this skill is useful
Adds specific benchmarking commands and performance measurement techniques that the AI wouldn't reliably generate on its own.
What it needs
Requires docker installed locally. About 2k tokens when loaded. Last updated 2026-08-06. 238,342 stars on the source repository.
What this skill does
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: Mode 2: API Performance Benchmarks API endpoints: Mode 3: Build Performance Measures development feedback loop: Mode 4: Before/After Comparison Run before and after a change to measure impact: Output: 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
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills affaan-m/benchmark--376fd2