Apply systematic performance optimization techniques for Python and Rust code: estimation + profiling, API/bulk design, algorithmic wins, cache-friendly memory layout, fewer allocations, fast paths, caching, and compiler-friendly hot loops. Use for performance code reviews, refactors, and profiling-driven optimizations. Keywords: performance, latency, throughput, cache, allocation, memory layout, PyO3, msgspec, tokio, async, pprof, py-spy, perf.
Key Features
- Comprehensive skill evaluation and performance tracking
- Community-driven ratings and reviews
- Easy integration with Claude Code
- Regular updates and maintenance
Quick Start
TopRank Skills install dj-bolt/performance-optimizationchat Comments (0)
Sign in to join the discussion and leave a comment.
Skill Details
GitHub Stars
1.3k
GitHub Forks
62
Created
Mar 2026
Last Updated
il y a 3 mois
tools
tools debugging
Related Skills
Build your own?
Join 12,000+ developers contributing to the Claude ecosystem.
No comments yet. Be the first to share your thoughts!