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performance-expert

Expert in performance optimization for React, Next.js, NestJS applications covering frontend rendering, API response times, database queries, and infrastructure optimization

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shipshitdev/v0
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23 juillet 2026 à 16:41
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anglais
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SKILL.md
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name
performance-expert
description
Expert in performance optimization for React, Next.js, NestJS applications covering frontend rendering, API response times, database queries, and infrastructure optimization
metadata
{"version":"1.0.0","tags":"performance, optimization, fullstack"}
# Performance Expert Skill Expert in performance optimization for React, Next.js, NestJS applications, MongoDB, and AWS infrastructure. ## When to Use This Skill - Optimizing React components or Next.js pages - Improving API response times - Optimizing database queries - Analyzing bundle sizes - Implementing caching strategies - Optimizing images or assets - Configuring CDN or caching - Reviewing Core Web Vitals ## Project Context Discovery 1. Check `.agents/memory/` for performance architecture context (e.g., `repo_frontend_design_execution.md`, any `*performance*` or `*architecture*` files) 2. Identify performance tools (Lighthouse CI, APM) 3. Review existing optimizations and caching strategies 4. Check for `[project]-performance-expert` skill ## Core Performance Principles ### Frontend (React/Next.js) **Bundle Optimization:** Code splitting, dynamic imports, tree shaking, remove unused deps **React Optimization:** useMemo, useCallback, React.memo, virtualization, lazy loading **Next.js:** Server Components, SSG, ISR, next/image, font optimization **Assets:** WebP images, font subset, CSS minify, Gzip/Brotli ### Backend (NestJS) **API Response Times:** Target < 200ms (p95), caching, background jobs, connection pooling **Query Optimization:** Indexes, projections, pagination, optimized aggregations ### Database (MongoDB) **Indexes:** On frequently queried fields, compound indexes, monitor usage **Queries:** Early $match, projection before expensive ops, sort with indexes ### Infrastructure (AWS) **CDN:** CloudFront caching, cache headers, edge optimization **Lambda:** Cold start optimization, memory allocation, provisioned concurrency ## Performance Metrics ### Frontend (Core Web Vitals) - **LCP:** < 2.5s - **FID:** < 100ms - **CLS:** < 0.1 - **FCP:** < 1.8s ### Backend - **API p50:** < 100ms - **API p95:** < 200ms - **DB Query p95:** < 50ms - **Error Rate:** < 0.1% ## Quick Checklist ### Frontend - [ ] Bundle size < 200KB initial - [ ] Code splitting implemented - [ ] Images optimized and lazy loaded - [ ] React components memoized ### Backend - [ ] Database queries optimized - [ ] Indexes created and used - [ ] Caching implemented - [ ] Background jobs for heavy operations --- **For complete React memoization patterns, Next.js optimization examples, database query optimization code, caching strategy implementation, N+1 query solutions, performance testing commands, and detailed checklists, see:** `references/full-guide.md`
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