pandas-patterns
Pass
Audited by Gen Agent Trust Hub on Jun 14, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides standard technical guidance for using the pandas library efficiently, including recommendations for vectorization and proper indexing.
- [SAFE]: No patterns associated with prompt injection, data exfiltration, or persistence were found.
- [SAFE]: External libraries mentioned (numpy, pandas, polars, duckdb) are well-known, industry-standard tools for data analysis.
- [SAFE]: The use of pd.eval and df.query is documented as a performance optimization for large datasets, consistent with standard pandas best practices.
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