Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
8.7
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Data & Analytics
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Exceptional cheminformatics skill with comprehensive coverage of datamol's capabilities. The SKILL.md provides crystal-clear descriptions that enable a CLI agent to invoke all major functions confidently. Task knowledge is outstanding with concrete code examples for every workflow (molecule handling, I/O, descriptors, fingerprints, clustering, scaffolds, conformers, visualization, reactions). The structure is logical with well-organized sections and appropriate delegation to reference files for detailed APIs. The skill demonstrates strong novelty by wrapping complex RDKit operations into simplified workflows that would otherwise require substantial token usage and domain expertise. Complete pipelines (SAR analysis, virtual screening, ML integration) add significant practical value. Minor deduction in structure for SKILL.md length (~500 lines), though justified by the domain's complexity. The skill would meaningfully reduce both cost and cognitive load for drug discovery tasks.
davila7
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