Molfeat

What it does

When your agent uses it

• Tasks that involve Drug discovery and cheminformatics
• Tasks that involve Embeddings

Example prompts

• “Use the molfeat skill to featuriz small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML”
• “/molfeat”

Requirements

• Python 3
• Compatibility (from SKILL.md): Requires Python 3.11+ and molfeat 1.0.0 (RDKit, datamol, PyTorch). macOS Intel needs Python 3.11–3.12 and upstream platform-specific dependency pins. Optional extras and network access are needed for pretrained models; core fingerprints run offline.
• Pre-approved tools (allowed-tools): Read, Write, Edit, Bash

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Preserve source record IDs, labels, original structures, and a declared policy for
2. 2Start with an explicit ECFP baseline. A calculator processes one molecule;
3. 3Record rejected positions and align every associated array. Inspect descriptor
4. 4Fit any feature selection, imputation, scaling, and model inside the training fold.
5. 5Save the featurizer state, ordered feature names, package versions, molecular

What it can do on your machine

Read from SKILL.md and the folder at commit 92ace75. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Write
  • Edit
  • Bash

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • uv

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • github.com
  • arxiv.org
  • pypi.org
  • doi.org
  • export.arxiv.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Requires Python 3.11+ and molfeat 1.0.0 (RDKit, datamol, PyTorch). macOS Intel needs Python 3.11–3.12 and upstream platform-specific dependency pins. Optional extras and network access are needed for pretrained models; core fingerprints run offline.

  From compatibility in the SKILL.md frontmatter.

Context cost

Molfeat loads about 2.4k tokens when it runs, and up to ~8.1k if it reads all its reference files. Until then it costs about 68 tokens; SKILL.md has 903 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~68

When it runs · the whole SKILL.md, loaded when a task matches

~2.4k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~8.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NotePre-approves every shell command (allowed-tools: Bash)SKILL.md

  allowed-tools: Read, Write, Edit, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from K-Dense-AI/scientific-agent-skills at commit 92ace75, republished under its Apache-2.0 licence (© K-Dense-AI). 903 words, ~2,371 tokens.

name

molfeat

description

Featurizes small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML. Covers ECFP/MACCS fingerprints, RDKit descriptors, pharmacophores, pretrained embeddings, configuration persistence, and molecule-to-label alignment.

allowed-tools

Read, Write, Edit, Bash

compatibility

Requires Python 3.11+ and molfeat 1.0.0 (RDKit, datamol, PyTorch). macOS Intel needs Python 3.11–3.12 and upstream platform-specific dependency pins. Optional extras and network access are needed for pretrained models; core fingerprints run offline.

license

Apache-2.0 license

metadata.version

2.0

metadata.skill-author

K-Dense Inc.

metadata.last-reviewed

2026-10-01

metadata.upstream-version

1.0.0

uv venv --python 3.13 .venv-molfeat
uv pip install --python .venv-molfeat/bin/python "molfeat==1.0.0"

import numpy as np
from molfeat.calc import FPCalculator
from molfeat.trans import MoleculeTransformer

smiles = ["CCO", "invalid", "CC(=O)O", "c1ccccc1"]
record_ids = np.array(["ethanol", "rejected", "acetate", "benzene"])
y = np.array([0.1, 9.9, 0.2, 0.3])  # toy labels only
calc = FPCalculator("ecfp", radius=2, fpSize=2048, includeChirality=True)
transformer = MoleculeTransformer(calc, n_jobs=1, dtype=np.float32)
X, valid_ids = transformer(smiles, ignore_errors=True)
assert X.shape == (3, 2048)
X_ids, y_valid = record_ids[valid_ids], y[valid_ids]
assert valid_ids == [0, 2, 3]
assert np.isfinite(X).all()

transformer.to_state_yaml_file("featurizer.yml")
loaded = MoleculeTransformer.from_state_yaml_file("featurizer.yml")
np.testing.assert_array_equal(loaded(["CCO"]), transformer(["CCO"]))

from molfeat.trans.pretrained import PretrainedHFTransformer

embedder = PretrainedHFTransformer(
    kind="ChemBERTa-77M-MLM", pooling="mean", concat_layers=-1,
    device="cpu", max_length=128, preload=False,
)
# First inference downloads/loads the model.
# embeddings = embedder(["CCO", "c1ccccc1"])

© K-Dense-AI, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/molfeat of K-Dense-AI/scientific-agent-skills.

• SKILL.md
• references/api_reference.md
• references/available_featurizers.md
• references/choosing_a_featurizer.md
• references/examples.md

Open the folder on GitHubat commit 92ace75

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in K-Dense-AI/scientific-agent-skills, which our catalogue first saw on October 7, 2026.

• lingxling/awesome-skills-cnclaude-scientific-skills/skills/molfeat