scvelo
Pass
Audited by Gen Agent Trust Hub on Mar 31, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill utilizes established and well-regarded scientific Python libraries including scvelo, scanpy, numpy, and matplotlib for genomic data analysis. No unverified or suspicious third-party dependencies were found.
- [SAFE]: The Python workflow script performs legitimate data processing, analysis, and visualization. File system operations are localized to reading user-provided genomic data formats (loom, h5ad) and writing results to a specified output directory.
- [SAFE]: Remote data access occurs through the library's built-in dataset loader
scv.datasets.pancreas(), which fetches example data from the official developer repository for demonstration purposes. - [SAFE]: No evidence of prompt injection, code obfuscation, persistence mechanisms, or unauthorized data exfiltration was identified within the documentation or the implementation scripts.
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