performance-optimization

📁 srstomp/pokayokay 📅 Jan 24, 2026
15
总安装量
7
周安装量
#22660
全站排名
安装命令
npx skills add https://github.com/srstomp/pokayokay --skill performance-optimization

Agent 安装分布

claude-code 3
codex 3
trae 2
antigravity 2
windsurf 2
github-copilot 2

Skill 文档

Performance Optimization

Systematic approach to identifying and fixing performance bottlenecks.

Key Principles

  • Measure first — Never optimize without data; establish baseline metrics
  • Identify bottleneck type — Network, CPU, memory, I/O, or rendering
  • One change at a time — Apply targeted fix, re-measure, compare against baseline
  • Quick wins first — Check compression, caching, indexes, N+1 queries before deep optimization

Core Web Vitals Targets

Metric Good Poor
LCP (Largest Contentful Paint) < 2.5s > 4.0s
INP (Interaction to Next Paint) < 200ms > 500ms
CLS (Cumulative Layout Shift) < 0.1 > 0.25

Quick Start Checklist

  1. Measure baseline (Lighthouse, RUM data, or APM)
  2. Identify bottleneck type: network, CPU, memory, I/O, or rendering
  3. Check quick wins: compression, caching headers, indexes, N+1 queries
  4. Read relevant reference for deep optimization
  5. Apply fix, re-measure, validate improvement
  6. Set performance budgets and enforce in CI

References

Reference Description
frontend-perf.md Bundle analysis, rendering, Core Web Vitals
backend-perf.md Query optimization, caching, async patterns
load-testing.md k6, Artillery patterns, CI integration
profiling-guide.md Chrome DevTools, Node profiling, flame graphs