Agent skill
cpu-profiling
Profile CPU usage to identify hot spots and bottlenecks. Optimize code paths consuming most CPU time for better performance and resource efficiency.
Install this agent skill to your Project
npx add-skill https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/cpu-profiling
SKILL.md
CPU Profiling
Table of Contents
- Overview
- When to Use
- Quick Start
- Reference Guides
- Best Practices
Overview
CPU profiling identifies which functions consume most CPU time, enabling targeted optimization of expensive code paths.
When to Use
- High CPU usage
- Slow execution
- Performance regression
- Before optimization
- Production monitoring
Quick Start
Minimal working example:
Browser Profiling:
Chrome DevTools:
Steps:
1. DevTools → Performance
2. Click record
3. Perform action
4. Stop recording
5. Analyze flame chart
Metrics:
- Function call duration
- Call frequency
- Total time vs self time
Firefox Profiler:
- Built-in performance profiler
- Flame graphs
- Timeline view
- Export and share
React Profiler:
- DevTools → Profiler
- Component render times
- Phase: render vs commit
- Why component re-rendered
// ... (see reference guides for full implementation)
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| Profiling Tools | Profiling Tools |
| Analysis & Interpretation | Analysis & Interpretation |
| Optimization Process | Optimization Process |
| Monitoring & Best Practices | Monitoring & Best Practices |
Best Practices
✅ DO
- Follow established patterns and conventions
- Write clean, maintainable code
- Add appropriate documentation
- Test thoroughly before deploying
❌ DON'T
- Skip testing or validation
- Ignore error handling
- Hard-code configuration values
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
websocket-implementation
Implement real-time bidirectional communication with WebSockets including connection management, message routing, and scaling. Use when building real-time features, chat systems, live notifications, or collaborative applications.
refactor-legacy-code
Modernize and improve legacy codebases while maintaining functionality. Use when you need to refactor old code, reduce technical debt, modernize deprecated patterns, or improve code maintainability without breaking existing behavior.
Sentiment Analysis
Classify text sentiment using NLP techniques, lexicon-based analysis, and machine learning for opinion mining, brand monitoring, and customer feedback analysis
flask-api-development
Develop lightweight Flask APIs with routing, blueprints, database integration, authentication, and request/response handling. Use when building RESTful APIs, microservices, or lightweight web services with Flask.
ML Model Explanation
Interpret machine learning models using SHAP, LIME, feature importance, partial dependence, and attention visualization for explainability
Statistical Hypothesis Testing
Conduct statistical tests including t-tests, chi-square, ANOVA, and p-value analysis for statistical significance, hypothesis validation, and A/B testing
Didn't find tool you were looking for?