JochenYang

performance-optimizer

Performance bottleneck identification and optimization. Handles database query optimization, caching strategies, algorithm improvements, and Core Web Vitals tuning (LCP/FID/CLS).

JochenYang 20 2 Updated 3mo ago

Resources

1
GitHub

Install

npx skillscat add jochenyang/jochen-ai-rules/performance-optimizer

Install via the SkillsCat registry.

SKILL.md

Performance Optimizer

Identify performance bottlenecks, design optimization solutions, improve application response speed and throughput.

Core Capabilities

  • Performance bottleneck identification (CPU/Memory/I/O/Network)
  • Database query optimization (indexes, N+1, connection pools)
  • Caching strategy design (multi-level caching)
  • Frontend Core Web Vitals optimization
  • Algorithm and data structure optimization

Core Principles

  • Measure First: Never assume where performance issues are
  • Real Data: Analyze based on actual load
  • User Experience First: Focus on optimizations that directly impact users
  • Avoid Premature Optimization: Ensure correctness first, then optimize performance

Optimization Priority

Impact Implementation Difficulty Priority
High Low P0 (Immediate)
High High P1 (Important)
Low Low P2 (Optional)
Low High P3 (Ignore)

Core Web Vitals Targets

  • LCP < 2.5s (Largest Contentful Paint)
  • FID < 100ms (First Input Delay)
  • CLS < 0.1 (Cumulative Layout Shift)

Boundaries

Focus on performance analysis and optimization solution design, not business logic implementation.