Toxicology Agent for pharma drug safety profiling from SMILES. Computes RDKit ADMET descriptors (logP, TPSA, MW, HBD, HBA, rotatable bonds), Lipinski Rule of...
Security Analysis
high confidenceThe skill's code, instructions, and declared dependency align with its stated purpose (RDKit-based SMILES toxicology profiling); it contains no apparent data-exfiltration, secret access, or unrelated capabilities.
Name/description match the implementation: the SKILL.md and scripts/tox_agent.py perform RDKit descriptor calculations, Lipinski/Veber checks, QED, and simplified PAINS matching. Declared dependency (rdkit-pypi) is appropriate for the stated functionality and no unrelated credentials or binaries are requested.
The runtime instructions are narrowly scoped: run the provided Python script with a SMILES string. The SKILL.md does not instruct the agent to read unrelated files, access environment secrets, or call external network endpoints. The script only processes the input SMILES and returns a local JSON report.
No install spec is provided (instruction-only skill) which is low-risk. However, the declared dependency rdkit-pypi can be non-trivial to install (native/compiled components). The skill does not provide an automated install step—users must ensure RDKit is available in the runtime environment.
No environment variables, credentials, or config paths are requested. The operations performed are local molecule analyses and do not require external secrets or system-level access.
always is false and the skill does not request persistent/system-level privileges. It does not modify other skills or system configuration.
Guidance
This skill appears internally consistent and implements what it claims: a small RDKit-based SMILES toxicology profiler. Before installing/running: (1) ensure RDKit (rdkit-pypi or a proper RDKit build) is available in an isolated environment — RDKit often requires compiled binaries; (2) be aware PAINS checking is a simplified/mock subset (SKILL.md notes this limitation), and the reported risk label is coarse ('Low' vs 'Medium/High'); (3) no network calls or secret access are present in the code, so there is no obvious exfiltration risk, but verify you run it in a controlled environment and review dependencies you install. If you need production-grade PAINS/QSAR/hERG or mutagenicity predictions, plan to replace the simplified implementations with validated models and a complete PAINS catalog.
Latest Release
v1.0.0
- Initial release of the pharmaclaw-tox-agent skill for drug safety profiling from SMILES. - Computes key RDKit ADMET descriptors, evaluates Lipinski and Veber rules, QED drug-likeness score, and PAINS alerts. - Provides clear risk classification (Low/Medium/High) with a detailed property report. - Integrates into PharmaClaw pipeline, receiving SMILES from Chemistry Query and supporting IP Expansion for safer analogs. - Offers a command-line script for easy analysis and supports chain-based workflow integration.
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