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Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
Passed 20 of 22 test cases with the skill, and 9 of 22 without it.
and 16 more in the full report
12 fixed8 passed either way1 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am creating a fresh Conda/uv Python environment for a project that relies on molfeat 0.11.0. What Python versions are supported by molfeat 0.11.0? Write a brief explanation or requirement specification.
| Checked | Without skill | With skill |
|---|---|---|
| Specifies Python 3.9 as a supported Python version | Passed | Passed |
| States that Python 3.11 is unsupported by molfeat 0.11.0 | Missed | Passed |
The instructions your model reads when the skill loads.
Molfeat is a comprehensive Python library for molecular featurization that unifies 100+ pre-trained embeddings and hand-crafted featurizers. Convert chemical structures (SMILES strings or RDKit molecules) into numerical representations for machine learning tasks including QSAR modeling, virtual screening, similarity searching, and deep learning applications. Features fast parallel processing, scikit-learn compatible transformers, and built-in caching.
Version note: Examples target molfeat 0.11.0 (PyPI stable, May 2025). Requires Python 3.9–3.10 (requires-python caps below 3.11). Depends on datamol ≥0.8.0 and PyTorch ≥1.13. Since 0.8.7, prefer datamol Mol objects over raw rdkit.Chem.Mol. Since 0.10.1, fingerprint calculators use RDKit's rdFingerprintGenerator API internally. Since 0.11.0, pretrained models load in memory and base models are set to PyTorch evaluation mode automatically.
This skill should be used when working with:
Use a Python 3.9 or 3.10 environment (molfeat does not install on 3.11+ as of 0.11.0):
uv pip install "molfeat==0.11.0"
# With all pip-installable optional dependencies
uv pip install "molfeat[all]==0.11.0"
Optional dependency extras (PyPI):
molfeat[dgl] — GNN models (GIN variants); upstream recommends dgl<=2.0 (graphbolt issues in newer DGL)molfeat[graphormer] — Graphormer modelsmolfeat[transformer] — ChemBERTa, ChemGPT, MolT5molfeat[fcd] — FCD descriptorsmolfeat[pyg] — PyTorch Geometric featurizersmolfeat[viz] — NGLView visualization widgetsExternal featurizers: MAP4 is not bundled in molfeat extras — install from reymond-group/map4 separately. Some heavy deps (DGL, dgllife, graphormer-pretrained) are easier via conda-forge; see optional dependencies.
test cases passed, vs 9 / 22 without
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