python-performance-optimization

Quick Review

This is a high-quality, comprehensive skill for Python performance optimization. It provides extensive task knowledge with 20+ concrete code patterns covering profiling (cProfile, line_profiler, memory_profiler, py-spy), optimization techniques (list comprehensions, generators, caching, NumPy), and best practices. The description clearly indicates when to use the skill (debugging slow code, optimizing bottlenecks), and the content is well-structured with clear sections and runnable examples. The skill is moderately novel - while a CLI agent could perform basic profiling, this consolidates best practices, comparative benchmarks, and production-ready patterns that would require significant token usage and domain expertise to replicate. The structure is logical with progressive complexity from basic timing to advanced multiprocessing. Minor improvement areas: could benefit from a quick reference index at the top for the 20 patterns, and some patterns could be extracted to separate files for a cleaner overview, though the current single-file approach is acceptable given clear section headers.