This is a Pythonic wrapper around RDKit that handles the everyday cheminformatics grunt work: parsing SMILES, standardizing structures, computing descriptors and fingerprints, clustering compounds, and generating 3D conformers. It returns native RDKit Mol objects so you can drop down to raw RDKit when you need fine control. The API is cleaner than vanilla RDKit (compare `dm.to_mol()` and `dm.standardize_mol()` to the RDKit equivalents), includes built-in parallelization for batch operations, and supports reading from S3 or GCS via fsspec. Good for drug discovery workflows where you're processing datasets and don't want to write boilerplate. Requires Python 3.8+ and installs RDKit automatically as a dependency.
- skills.sh installs
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- last updated
- Aug 21, 2026
Install
$ npx -y skills add k-dense-ai/scientific-agent-skills --skill datamol --agent claude-codeInstalls into .claude/skills of the current project.
Files
Datamol Cheminformatics Skill
Overview
Datamol is a Python library that provides a lightweight, Pythonic abstraction layer over RDKit for molecular cheminformatics. Simplify complex molecular operations with sensible defaults, efficient parallelization, and modern I/O capabilities. All molecular objects are native rdkit.Chem.Mol instances, ensuring full compatibility with the RDKit ecosystem.
Verified target: datamol 0.13.0, released September 9, 2026. Local checks used Python 3.13 and RDKit 2026.03.6. Python 3.11+ and RDKit 2024.09+ are required. The 0.13 distribution includes SELFIES, visualization, cloud, Excel and Parquet runtime dependencies. Current API examples and verification limits are recorded in references/review.md. Pin the environment: RDKit upgrades can change canonical representations and retained conformers. Compare chemical invariants, not a fixed conformer count or an exact version-dependent canonical string.
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- Repository
- github.com/k-dense-ai/scientific-agent-skills
- Categories
- AI & Agent Building, Data Science & ML, Automation & Workflows, Sales & Marketing
- First seen
- Jun 3, 2026
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