srstomp

performance-optimization

Use when analyzing performance issues, optimizing slow pages or APIs, setting up load testing (k6, Artillery), implementing caching, reducing bundle sizes, establishing performance budgets, or profiling bottlenecks. Covers frontend (Core Web Vitals, rendering, bundle size) and backend (query optimization, caching, async patterns) optimization.

srstomp 7 2 Updated 3mo ago

Resources

1
GitHub

Install

npx skillscat add srstomp/pokayokay/performance-optimization

Install via the SkillsCat registry.

SKILL.md

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