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web-performance-audit · aj-geddes — Claude Code skill: audit page speed

This skill measures page load times, finds bottlenecks and points at what to fix. Useful after a big release or when users complain about slowness.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add aj-geddes/useful-ai-prompts --skill web-performance-audit -a claude-code
Open on GitHub

What web-performance-audit does

The skill runs a web performance audit: it measures load times, identifies bottlenecks and recommends optimizations. It leans on Google's Core Web Vitals — LCP, FID and CLS — with good and poor thresholds for each. LCP under 2.5 seconds is good, over 4 seconds is poor.

Four reference guides ship in the references/ directory: performance metrics, the analysis process, optimization strategies, and monitoring with continuous improvement. The skill tells you to measure regularly rather than once, combine field data from real users with lab data, test on slow networks and include mobile. It also warns against optimizing without measurement and chasing a single metric.

Install goes through npx skills add or gh skill install, with a separate command per platform. Without access to real load data the skill stays a set of recommendations — you still have to collect the numbers it works from.

What it helps with

  • measure LCP, FID and CLS on key pages
  • find bottlenecks after a major release
  • figure out why users report slow loading
  • set a performance baseline before optimizing
  • check mobile speed separately from desktop

Example prompts for the agent

  • Audit the homepage performance and show which Core Web Vitals are failing
  • Pull field and lab data for the product listing page and tell me what to optimize first
  • Draft a performance monitoring plan and metric budgets for the mobile site

How to install web-performance-audit

1Skills CLI (Vercel)

npx skills add aj-geddes/useful-ai-prompts --skill web-performance-audit -a claude-code

2Manually: put the files in place

~/.claude/skills/web-performance-audit/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/web-performance-audit/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about web-performance-audit

How do I install web-performance-audit in Claude?

Run npx skills add aj-geddes/useful-ai-prompts --skill web-performance-audit -a claude-code. The skill file lands at ~/.claude/skills/web-performance-audit/SKILL.md.

What does web-performance-audit do?

It audits web performance: measures load speed, identifies bottlenecks and recommends optimizations. It works from Core Web Vitals and field data.

Which metrics does it focus on?

Core Web Vitals: LCP, FID and CLS. Each metric comes with good and poor thresholds, and the skill also mentions FCP and other additional metrics.

Source text

SKILL.md · MIT
---
name: web-performance-audit
description: >
  Conduct comprehensive web performance audits. Measure page speed, identify
  bottlenecks, and recommend optimizations to improve user experience and SEO.
---

# Web Performance Audit

## Table of Contents

- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)

## Overview

Web performance audits measure load times, identify bottlenecks, and guide optimization efforts to create faster, better user experiences.

## When to Use

- Regular performance monitoring
- After major changes
- User complaints about slowness
- SEO optimization
- Mobile optimization
- Performance baseline setting

## Quick Start

Minimal working example:

```yaml
Core Web Vitals (Google):

Largest Contentful Paint (LCP):
  Measure: Time to load largest visible element
  Good: <2.5 seconds
  Poor: >4 seconds
  Impacts: User perception of speed

First Input Delay (FID):
  Measure: Time from user input to response
  Good: <100 milliseconds
  Poor: >300 milliseconds
  Impacts: Responsiveness

Cumulative Layout Shift (CLS):
  Measure: Visual stability (unexpected layout shifts)
  Good: <0.1
  Poor: >0.25
  Impacts: User frustration

---

Additional Metrics:

First Contentful Paint (FCP):
// ... (see reference guides for full implementation)
```

## Reference Guides

Detailed implementations in the `references/` directory:

| Guide | Contents |
|---|---|
| [Performance Metrics](references/performance-metrics.md) | Performance Metrics |
| [Performance Analysis Process](references/performance-analysis-process.md) | Performance Analysis Process |
| [Optimization Strategies](references/optimization-strategies.md) | Optimization Strategies |
| [Monitoring & Continuous Improvement](references/monitoring-continuous-improvement.md) | Monitoring & Continuous Improvement |

## Best Practices

### ✅ DO

- Measure regularly (not just once)
- Use field data (real users) + lab data
- Focus on Core Web Vitals
- Set realistic targets
- Prioritize by impact
- Monitor continuously
- Setup performance budgets
- Test on slow networks
- Include mobile in testing
- Document improvements

### ❌ DON'T

- Ignore field data
- Focus on one metric only
- Set impossible targets
- Optimize without measurement
- Forget about images
- Ignore JavaScript costs
- Skip mobile performance
- Over-optimize prematurely
- Forget about monitoring
- Expect improvements without effort

© aj-geddes · MIT · aj-geddes/useful-ai-prompts

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