molfeat-molecular-featurization
Pass
Audited by Gen Agent Trust Hub on Sep 18, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill utilizes the legitimate
molfeatlibrary for molecular featurization, which is a standard tool in the cheminformatics community. All library functions and examples provided are consistent with its official documentation. - [SAFE]: Installation instructions use
uv pip install molfeatand official extras, pointing to valid packages on PyPI. There are no signs of typosquatting or malicious dependencies. - [SAFE]: External references to
datamol.ioand associated GitHub repositories are authentic and belong to the primary developers of the library. - [SAFE]: Network operations are confined to downloading model weights through the library's official
ModelStoreAPI, which is a necessary and documented feature for the skill's purpose. - [SAFE]: The skill processes molecular SMILES data through its transformer interface, with sanitization implicitly managed by the underlying chemical parsing logic which validates molecular structures.
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