Performance optimizer
Skill JochenYang/Jochen-ai-rules/skills/performance-optimizer
Performance bottleneck identification and optimization. Handles database query optimization, caching strategies, algorithm improvements, and Core Web Vitals tuning (LCP/FID/CLS). Use when user asks to optimize performance, improve speed, fix slow queries, or tune web vitals.From its SKILL.md
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SKILL.md
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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.
When NOT to Use
- Writing new features → use
developer - Frontend UI implementation → use
frontend-design - API design → use
api-designer - Database schema design → use
database-engineer - Security auditing → use
quality-assurance
Escalation Rules
Pause and ask the owner before:
- making optimization changes without measurement evidence
- trading correctness, readability, or maintainability for marginal speed gains
- expanding hotspot tuning into a broad refactor without scope agreement
Final Output Contract (MANDATORY)
Every use of this skill should end with:
Skill Fit- why performance work is the right focusPrimary Deliverable- bottleneck analysis, optimization plan, or implemented improvementExecution Evidence- metrics, profiling data, and validation checks usedRisks / Open Questions- measurement gaps, regression risk, or scaling uncertaintyNext Action- the next benchmark, fix, or review step