#601

Globales Ranking · von 601 Skills

frontend-performance AI Agent Skill

Quellcode ansehen: b-open-io/prompts

Safe

Installation

npx skills add b-open-io/prompts --skill frontend-performance

89

Installationen

Frontend Performance Optimization

Diagnose and fix performance issues in Next.js applications.

Quick Diagnostics

Run Lighthouse CLI

# Performance audit (headless)
npx lighthouse http://localhost:3000 --output=json --output-path=./lighthouse.json --chrome-flags="--headless" --only-categories=performance

# Parse key metrics
cat lighthouse.json | jq '{
  score: .categories.performance.score,
  FCP: .audits["first-contentful-paint"].displayValue,
  LCP: .audits["largest-contentful-paint"].displayValue,
  TBT: .audits["total-blocking-time"].displayValue,
  CLS: .audits["cumulative-layout-shift"].displayValue
}'

# Find slow scripts
cat lighthouse.json | jq '.audits["bootup-time"].details.items | .[0:8]'

# Main thread breakdown
cat lighthouse.json | jq '.audits["mainthread-work-breakdown"].details.items'

Important: Always test production builds (next build && next start), not dev mode. Dev mode has 2-10x overhead from HMR, source maps, and no optimizations.

Bundle Analysis

# Install
bun add -d @next/bundle-analyzer

# Run analysis
ANALYZE=true bun run build

Configure in next.config.js:

import bundleAnalyzer from '@next/bundle-analyzer'

const withBundleAnalyzer = bundleAnalyzer({
  enabled: process.env.ANALYZE === 'true',
})

export default withBundleAnalyzer(nextConfig)

Common Fixes

1. optimizePackageImports

For libraries with many exports (icons, utilities, animation libraries):

// next.config.js
const nextConfig = {
  experimental: {
    optimizePackageImports: [
      'framer-motion',
      'lucide-react',
      '@phosphor-icons/react',
      'lodash',
      'date-fns',
      '@heroicons/react',
    ],
  },
}

This ensures tree-shaking works correctly - only imports you use get bundled.

2. Framer Motion - Variants Pattern

WRONG - Creates N animation controllers:

// Each element has its own animation state - expensive!
{items.map((item, i) => (
  <motion.div
    key={i}
    initial={{ opacity: 0, y: 20 }}
    animate={{ opacity: 1, y: 0 }}
    transition={{ delay: i * 0.05 }}  // Individual delays
  >
    {item}
  </motion.div>
))}

RIGHT - Single controller with staggerChildren:

// Parent controls all children - efficient!
const containerVariants = {
  hidden: {},
  visible: {
    transition: {
      staggerChildren: 0.05,
    },
  },
}

const itemVariants = {
  hidden: { opacity: 0, y: 20 },
  visible: {
    opacity: 1,
    y: 0,
    transition: { type: 'spring' as const, damping: 15 }
  },
}

<motion.div
  variants={containerVariants}
  initial="hidden"
  animate="visible"
>
  {items.map((item, i) => (
    <motion.div key={i} variants={itemVariants}>
      {item}
    </motion.div>
  ))}
</motion.div>

Also avoid:

  • filter: blur() in animations - very expensive
  • Too many infinite animations (reduce or use CSS)
  • Individual transition props on children when using variants

3. Move Heavy Computation Server-Side

Keep these out of client bundles:

  • Syntax highlighting: use shiki server-side, not prism-react-renderer
  • Markdown parsing: render on server
  • Date formatting libraries: consider Intl.DateTimeFormat
  • Large data transformations: API routes or server components

4. Image Optimization

// Always use next/image
import Image from 'next/image'

<Image
  src="/hero.jpg"
  alt="Hero"
  width={1200}
  height={600}
  priority  // For LCP images
  placeholder="blur"  // Reduces CLS
/>

5. Font Optimization

// app/layout.tsx
import { Inter } from 'next/font/google'

const inter = Inter({
  subsets: ['latin'],
  display: 'swap',  // Prevents FOIT
  preload: true,
})

6. External Packages (Server Only)

Prevent server-only packages from being bundled:

// next.config.js
const nextConfig = {
  serverExternalPackages: ['sharp', 'canvas'],
}

Performance Targets

Metric Good Needs Improvement Poor
LCP ≤2.5s 2.5-4s >4s
FCP ≤1.8s 1.8-3s >3s
TBT ≤200ms 200-600ms >600ms
CLS ≤0.1 0.1-0.25 >0.25

Debugging Workflow

  1. Run production Lighthouse - Get baseline metrics
  2. Check bootup-time audit - Find slow scripts
  3. Run bundle analyzer - Identify large chunks
  4. Fix largest issues first - Usually 1-2 packages cause most problems
  5. Re-test - Verify improvements

Quick Wins Checklist

  • Test production build, not dev
  • Add optimizePackageImports for icon/utility libraries
  • Use Framer Motion variants pattern
  • Remove filter: blur() from animations
  • Add priority to LCP images
  • Use next/font with display: swap
  • Move heavy libraries to server components

Installationen

Installationen 89
Globales Ranking #601 von 601

Sicherheitsprüfung

ath Safe
socket Safe
Warnungen: 0 Bewertung: 90
snyk Low
zeroleaks Safe
Bewertung: 93
EU EU-Hosted Inference API

Power your AI Agents with the best open-source models.

Drop-in OpenAI-compatible API. No data leaves Europe.

Explore Inference API

GLM

GLM 5

$1.00 / $3.20

per M tokens

Kimi

Kimi K2.5

$0.60 / $2.80

per M tokens

MiniMax

MiniMax M2.5

$0.30 / $1.20

per M tokens

Qwen

Qwen3.5 122B

$0.40 / $3.00

per M tokens

So verwenden Sie diesen Skill

1

Install frontend-performance by running npx skills add b-open-io/prompts --skill frontend-performance in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.

2

Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.

3

Der Skill verbessert das Verständnis Ihres Agenten für frontend-performance, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.

Was Sie erhalten

Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.

Kompatibilität

Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.

EU Made in Europe

Chat with 100+ AI Models in one App.

Use Claude, ChatGPT, Gemini alongside with EU-Hosted Models like Deepseek, GLM-5, Kimi K2.5 and many more.

App herunterladen:

Kundensupport