Web Performance Audit

This walks you through a structured web performance audit covering Core Web Vitals like LCP, FID, and CLS, plus the full analysis process from measurement to optimization. You'd pull this out when diagnosing slow page loads, prepping for SEO work, or setting performance baselines after a major deploy. The real value is in the reference guides that break down metrics, analysis workflows, and specific optimization strategies. It's heavy on the "what to measure and why" side, which is actually helpful since most teams jump straight to guessing at fixes without proper measurement. One honest take: the emphasis on field data plus lab data and continuous monitoring is the right approach, even if it feels like more work upfront.

skills.sh installs: 548
GitHub stars: 379
last updated: Aug 21, 2026

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Install

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

Installs into .claude/skills of the current project.

Files

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:

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

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Additional Metrics:

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