manastalukdar/ai-devstudio/performance-profile

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