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performance-auditor

Skill1 starsChanged 5 months agoApache-2.0View on GitHub

Audits web application performance and generates an actionable improvement plan. Use when a web app is slow, fails Lighthouse checks, or has poor Core Web Vitals scores.

3 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 1 is distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Add web-vitals library and log to console or analytics.

    line 40
  2. Distinctive:

    Look for: render-blocking resources, large unoptimized images, many small requests, no compression, long TTFB.

    line 49
  3. Very specific:

    Check Cache-Control, ETag, Last-Modified.

    line 52
  4. Very specific:

    Use next/image or <picture> + modern formats (AVIF, WebP).

    line 56

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Overview

Performs a structured performance audit using Lighthouse, the web-vitals library, bundle analyzers, network waterfall analysis, and caching review. Produces a prioritized, actionable fix list with estimated impact and implementation effort for each issue.

When to Use This Skill

  • A page or app feels slow.
  • Lighthouse score is low (<90 in Performance).
  • User complains about load time, interactivity, or layout shift.
  • Preparing for a performance budget or before a major launch.

Prerequisites

  • The running application (local dev or deployed preview).
  • Node.js for running Lighthouse CLI.
  • Access to build output for bundle analysis.
  • Browser DevTools.

Steps

  1. Run Lighthouse:
    npx lighthouse https://example.com --view --preset=desktop
npx lighthouse https://example.com --view --preset=mobile
  2. Measure real user metrics:
    • Add web-vitals library and log to console or analytics.
    • Or use Chrome DevTools Performance panel + Web Vitals extension.
  3. Bundle analysis:
    • For webpack/Next.js: next build + ANALYZE=true or webpack-bundle-analyzer.
    • Identify large dependencies, duplicate code, unused exports.
  4. Network waterfall review:
    • Record in DevTools Network tab (disable cache).
    • Look for: render-blocking resources, large unoptimized images, many small requests, no compression, long TTFB.
  5. Caching & headers audit:
    • Check Cache-Control, ETag, Last-Modified.
    • Recommend immutable assets for hashed files, stale-while-revalidate for others.
  6. Image & media optimization:
    • Use next/image or <picture> + modern formats (AVIF, WebP).
    • Proper width/height or aspect-ratio to prevent CLS.
    • Lazy loading.
  7. JavaScript & interactivity:
    • Code splitting, dynamic imports.
    • Defer non-critical scripts.
    • Optimize event handlers and re-renders (React Profiler).
  8. Generate prioritized fix list:
    • Format: Issue | Current metric | Target | Effort | Impact | How to fix (concrete steps).
  9. Output:
    • Lighthouse report summary.
    • Bundle size breakdown.
    • Specific code patches for top 5-7 issues.
    • Monitoring recommendation (add web-vitals to analytics).

Examples

Sample Lighthouse command output interpretation, a typical "top issues" report, and concrete fixes (e.g., "Replace this 1.2MB hero image with next/image + AVIF", "Add loading="lazy" to below-the-fold images", "Split this heavy modal into dynamic import") are provided.

Edge Cases & Error Handling

  • Third-party scripts: Identify and suggest async/defer or partytown.
  • Large vendor bundles: Recommend tree-shaking, replacing heavy libs (e.g., moment → date-fns).
  • SPA vs MPA: Different strategies for each.

Verification

  1. Re-run Lighthouse after fixes — score improvement documented.
  2. Measure LCP, CLS, INP before/after with web-vitals.
  3. Bundle size reduced (compare next build output).
  4. Real user metrics improve in analytics.
  5. Success: Measurable, sustained improvement in user-perceived performance.

References

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