Skip to content

k-dense-ai/drug-discovery-agent-skills

v1.3.0MIT

Agent Skills for small-molecule and protein therapeutics: target validation and human genetics, bioactivity and chemical space, generative design and retrosynthesis, docking, free energy and dynamics, ADMET and PK translation, protein, antibody, degrader and oligonucleotide design, and the clinical and regulatory record.

GitHubOpen Website
skills

molfeat

Molecular featurization hub with one consistent interface over 100+ featurizers. Fingerprints (ECFP/Morgan, MACCS, atom pair, topological torsion, Avalon, RDKit, ERG), RDKit and Mordred descriptor sets, pharmacophore and 3D shape descriptors, scaffold keys, and pretrained embeddings (ChemBERTa, ChemGPT, MolT5, GIN, Graphormer) through a common transformer API with caching and parallelism. Use this skill to convert SMILES into model-ready feature matrices for QSAR, virtual screening, and molecular ML, and to choose between featurizer families. Also trigger on molfeat, MoleculeTransformer, FPVecTransformer, PretrainedHFTransformer, molfeat model store, or featurizer selection.

Version
1.4
License
MIT
Compatibility
Requires Python 3.9–3.10 (molfeat 0.11.0 declares `requires-python <3.11`). Requires datamol, RDKit, and PyTorch; GNN and transformer featurizers need optional extras. The 8 HuggingFace models in the model store cannot be downloaded from it — see "Pretrained models" below.
Read SKILL.md at the source

Pinned to revision f67572246d9b, so it is the text this page describes rather than whatever the author pushed since.

Pre-approved tools experimental

Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.

  • Read
  • Write
  • Edit
  • Bash

Files

Every link opens the file at its source, pinned to the revision this page describes.