scientific-cheminformatics
Pass
Audited by Gen Agent Trust Hub on Jun 20, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: No malicious patterns were detected in the skill's code or instructions. The skill follows standard practices for scientific data analysis.
- [COMMAND_EXECUTION]: The provided code snippets use standard Python libraries (RDKit, Pandas, NumPy) for data processing. There are no instances of unsafe command execution, shell spawning, or dynamic code evaluation (e.g., eval/exec).
- [DATA_EXFILTRATION]: The skill writes analysis results to local files in the
results/directory (e.g.,tanimoto_similarity.csv). No network exfiltration or unauthorized data access patterns were identified. - [EXTERNAL_DOWNLOADS]: The documentation references well-known scientific databases and tools such as PubChem, ChEMBL, and ZINC. These are standard resources in the cheminformatics domain and do not represent a security risk.
Audit Metadata