benchmark
Helps your agent measure code speed and performance. It's useful for ensuring things are fast and finding slowness issues.
What it does
This tool measures the speed and performance of your website or app. It checks how fast pages load, how quickly APIs respond, and how fast your development process is.
When to use it
- ✓Before and after making a change to see its impact.
- ✓When users complain something feels slow.
- ✓To ensure performance is good before launching something new.
Example of what to ask your AI
“Measure my homepage speed and compare it to the baseline.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It simulates using your website or app and records various time and size measurements. It then compares these numbers to a previous record or defined goals.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add affaan-m/ECC --skill benchmarkOr download just the file:
curl -L https://raw.githubusercontent.com/affaan-m/ECC/main/pi/core/skills/benchmark/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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 compareon every PR - Pair with
/canary-watchfor post-deploy monitoring - Pair with
/browser-qafor full pre-ship checklist
FAQ
What are 'Core Web Vitals'?
These are important metrics that measure user experience regarding page loading speed, interactivity, and visual stability.
Where are the results stored?
Results are saved in plain text files (JSON) that are tracked by the version control system (Git), so everyone on the team can see them.
Can I compare different technologies?
Yes, you can use this tool to compare the performance of different approaches or technologies before deciding which one to use.
Details
Original description by the author
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.
repo: affaan-m/ECC
Popularity
- GitHub stars
- 280k
- Ranking position
- #17
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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