python-performance-optimization
Pass
Audited by Gen Agent Trust Hub on Jul 17, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill is a comprehensive guide for Python performance optimization. All code snippets demonstrate legitimate use cases for timing, profiling, and optimizing code using standard library modules (e.g., cProfile, timeit, multiprocessing, asyncio, sqlite3) and reputable third-party libraries.
- [EXTERNAL_DOWNLOADS]: The documentation suggests installing well-known and industry-standard Python packages for performance analysis, including
line-profiler,memory-profiler,py-spy, andpytest-benchmark. It also references common libraries likenumpy,aiohttp, andrequestsfor optimization examples. - [COMMAND_EXECUTION]: Provides examples of using diagnostic CLI tools such as
py-spyandkernprof. These are used appropriately for profiling process performance and do not involve arbitrary or hidden command execution.
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