Awesome-omni-skill performance-optimizer
Performance bottleneck identification and optimization. Handles database query optimization, caching strategies, algorithm improvements, and Core Web Vitals tuning (LCP/FID/CLS).
install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/development/performance-optimizer-jochenyang" ~/.claude/skills/diegosouzapw-awesome-omni-skill-performance-optimizer-f82fea && rm -rf "$T"
manifest:
skills/development/performance-optimizer-jochenyang/SKILL.mdsource content
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.