alterlab-deepchem

Pass

Audited by Gen Agent Trust Hub on Apr 12, 2026

Risk Level: SAFEEXTERNAL_DOWNLOADS
Full Analysis
  • [SAFE]: The skill is focused on academic and industrial chemistry research tasks. It utilizes established open-source libraries like DeepChem, PyTorch, and Scikit-Learn to perform molecular modeling without any evidence of malicious intent or hidden capabilities.
  • [EXTERNAL_DOWNLOADS]: The skill facilitates the downloading of standard benchmark datasets via the MoleculeNet API and pretrained molecular models from HuggingFace Hub (e.g., ChemBERTa and MolFormer). These operations are standard practices in machine learning and target well-known, community-vetted repositories.
  • [COMMAND_EXECUTION]: Included Python scripts provide structured interfaces for training and evaluation. They utilize standard argument parsing for configuration and do not involve the execution of arbitrary shell commands or external scripts beyond the documented machine learning workflows.
Audit Metadata
Risk Level
SAFE
Analyzed
Apr 12, 2026, 12:46 AM
Security Audit — agent-trust-hub — alterlab-deepchem