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Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including 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.
Passed 24 of 24 test cases with the skill, and 3 of 24 without it.
and 28 more in the full report
21 fixed3 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 21 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a Python code snippet that renders a molecular image while explicitly highlighting specific atom indices 0 through 3 and bond indices 0 through 2 on the 2D diagram.
| Checked | Without skill | With skill |
|---|---|---|
| dm.viz.to_image is called with highlight_atom=[0, 1, 2, 3]. | Missed | Passed |
| dm.viz.to_image is called with highlight_bond=[0, 1, 2]. | Missed | Passed |
The instructions your model reads when the skill loads.
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.
Version note: Examples target datamol 0.12.x (PyPI stable: 0.12.5, June 2024). Since 0.10.0, modules are lazy-loaded by default (set DATAMOL_DISABLE_LAZY_LOADING=1 to disable). Since 0.12.2, RDKit is a direct PyPI dependency of datamol. Fingerprints use RDKit's rdFingerprintGenerator API (0.12.5+).
Key capabilities:
Guide users to install datamol:
uv pip install datamol
RDKit is installed automatically with datamol. For remote file paths (S3, GCS, HTTP), install the matching fsspec backend:
uv pip install s3fs # AWS S3
uv pip install gcsfs # Google Cloud Storage
Import convention:
import datamol as dm
test cases passed, vs 3 / 24 without
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