py-data
Pass
Audited by Gen Agent Trust Hub on May 8, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill consists of educational material and code snippets for data analysis using established libraries such as pandas, Polars, and NumPy. No malicious patterns, obfuscation, or data exfiltration attempts were detected.
- [SAFE]: All external dependencies mentioned (polars, pandas, numpy, pyarrow, duckdb, connectorx, great_expectations, narwhals) are well-known, reputable packages in the data science ecosystem.
- [SAFE]: File operations are restricted to standard data formats (CSV, Parquet, JSON) and use local paths typical for data processing tasks.
- [SAFE]: No network exfiltration or sensitive credential harvesting patterns were found.
Audit Metadata