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performance-optimization

Full-stack performance analysis, optimization patterns, and monitoring strategies

aiskillstore☆ 122 Étoiles du dépôt6 Forks du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

Voir la source ↗Guides

Instructions

Performance Optimization Skill

Comprehensive frameworks for analyzing and optimizing application performance across the entire stack.

When to Use

  • Application feels slow or unresponsive
  • Database queries taking too long
  • Frontend bundle size too large
  • API response times exceed targets
  • Core Web Vitals need improvement
  • Preparing for scale or high traffic

Performance Targets

Core Web Vitals (Frontend)
Metric Good Needs Work
LCP (Largest Contentful Paint) < 2.5s < 4s
INP (Interaction to Next Paint) < 200ms < 500ms
CLS (Cumulative Layout Shift) < 0.1 < 0.25
TTFB (Time to First Byte) < 200ms < 600ms
Backend Targets
Operation Target
Simple reads < 100ms
Complex queries < 500ms
Write operations < 200ms
Index lookups < 10ms

Bottleneck Categories

Category Symptoms Tools
Network High TTFB, slow loading Network tab, WebPageTest
Database Slow queries, pool exhaustion EXPLAIN ANALYZE, pg_stat_statements
CPU High usage, slow compute Profiler, flame graphs
Memory Leaks, GC pauses Heap snapshots
Rendering Layout thrashing React DevTools, Performance tab

Database Optimization

Key Patterns
  1. Add Missing Indexes - Turn Seq Scan into Index Scan
  2. Fix N+1 Queries - Use JOINs or include instead of loops
  3. Cursor Pagination - Never load all records
  4. Connection Pooling - Manage connection lifecycle
Quick Diagnostics
-- Find slow queries (PostgreSQL)
SELECT query, calls, mean_time / 1000 as mean_seconds
FROM pg_stat_statements ORDER BY total_time DESC LIMIT 10;

-- Verify index usage
EXPLAIN ANALYZE SELECT * FROM orders WHERE user_id = 123;

See templates/database-optimization.ts for N+1 fixes and pagination patterns

Caching Strategy

Cache Hierarchy
L1: In-Memory (LRU, memoization) - fastest
L2: Distributed (Redis/Memcached) - shared
L3: CDN (edge, static assets) - global
L4: Database (materialized views) - fallback
Cache-Aside Pattern
const cached = await redis.get(key);
if (cached) return JSON.parse(cached);
const data = await db.query(...);
await redis.setex(key, 3600, JSON.stringify(data));
return data;

See templates/caching-patterns.ts for full implementation

Frontend Optimization

Bundle Optimization
  1. Code Splitting - lazy() for route-based splitting
  2. Tree Shaking - Import only what you need
  3. Image Optimization - WebP/AVIF, lazy loading, proper sizing
Rendering Optimization
  1. Memoization - memo(), useCallback(), useMemo()
  2. Virtualization - Render only visible items in long lists
  3. Batch DOM Operations - Read all, then write all

See templates/frontend-optimization.tsx for patterns

Analysis Commands
# Lighthouse audit
lighthouse http://localhost:3000 --output=json

# Bundle analysis
npx @next/bundle-analyzer  # Next.js
npx vite-bundle-visualizer # Vite

API Optimization

Response Optimization
  1. Field Selection - Return only requested fields
  2. Compression - Enable gzip/brotli (threshold: 1KB)
  3. ETags - Enable 304 responses for unchanged data
  4. Pagination - Cursor-based for large datasets

See templates/api-optimization.ts for middleware examples

Monitoring Checklist

Before Launch
  • Lighthouse score > 90
  • Core Web Vitals pass
  • Bundle size within budget
  • Database queries profiled
  • Compression enabled
  • CDN configured
Ongoing
  • Performance monitoring active
  • Alerting for degradation
  • Lighthouse CI in pipeline
  • Weekly query analysis
  • Real User Monitoring (RUM)

See templates/performance-metrics.ts for Prometheus metrics setup

Extended Thinking Triggers

Use Opus 4.5 extended thinking for:

  • Complex debugging - Multiple potential causes
  • Architecture decisions - Caching strategy selection
  • Trade-off analysis - Memory vs CPU vs latency
  • Root cause analysis - Performance regression investigation

Templates Reference

Template Purpose
database-optimization.ts N+1 fixes, pagination, pooling
caching-patterns.ts Redis cache-aside, memoization
frontend-optimization.tsx React memo, virtualization, code splitting
api-optimization.ts Compression, ETags, field selection
performance-metrics.ts Prometheus metrics, performance budget

Exemples

Consultez les exemples du dépôt source.

Voir la source ↗

Historique source

Date d’indexation
2026-01-20
Mise à jour de l’index
2026-01-28
Branch
main

Les dates concernent ce répertoire. Consultez le dépôt pour l’historique du code.

GitHub ↗

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