Performance profile
Performance profiling and bottleneck detection for Node.js, Python, and browser appsFrom its SKILL.md
npx -y skills add manastalukdar/ai-devstudio --skill performance-profileAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Performance Profiling & Bottleneck Detection
I'll profile your application to identify performance bottlenecks and provide optimization recommendations.
Supported Environments:
- Node.js profiling (--inspect, clinic.js)
- Browser performance (Chrome DevTools)
- Python profiling (cProfile, line_profiler)
- Bottleneck identification
- Memory leak detection
- Optimization recommendations
Arguments: $ARGUMENTS - optional: node|python|browser or specific file/route to profile
Token Optimization
Expected range: 400–2,500 tokens (initial), 200 tokens (cache hit)
Caching: Caches runtime detection in .claude/cache/performance-profile/runtime.json for 7 days. Invalidated when package.json changes.
Early exit: Returns immediately if the profiling environment is already configured.
Patterns used: Grep-before-Read, early exit, Bash for system queries, caching
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.