python-performance-optimization
Pass
Audited by Gen Agent Trust Hub on Oct 19, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides standard documentation and implementation patterns for Python performance optimization.
- [EXTERNAL_DOWNLOADS]: The implementation playbook mentions standard, well-known Python packages for profiling (line-profiler, memory-profiler, py-spy, pytest-benchmark) and optimization (numpy, aiohttp, requests). These are industry-standard tools appropriate for the skill's stated purpose.
- [COMMAND_EXECUTION]: The skill includes command-line examples for using profiling tools like
cProfile,kernprof, andpy-spy. These are standard development workflows. - [DATA_EXFILTRATION]: Network operations are limited to benchmark examples targeting 'https://httpbin.org', a well-known service used for testing HTTP requests. No sensitive data access or exfiltration patterns were detected.
- [DYNAMIC_EXECUTION]: The skill uses
timeit.timeit()andcProfile.Profile(), which are standard Python modules for measuring execution time and profiling code paths. The examples provided use static strings or function references.
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