Datamol

Datamol is a Data skill for Claude Code, published by K-Dense-AI in scientific-agent-skills.

33.5K stars3.3K forkson K-Dense-AI/scientific-agent-skillsAdded 2026/08/14Repository updated 2026/08/13

agent-skillsai-scientistbioinformaticschemoinformaticsclaudeclaude-skillsclaudecodeclinical-researchcomputational-biologydata-analysisdrug-discoverygenomicsmaterials-sciencemetabolomicsproteomicsscientific-computingscientific-visualization

Install in seconds

Install Datamol

Copy Datamol into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/datamol ~/.claude/skills/datamol

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/datamol/SKILL.md in K-Dense-AI/scientific-agent-skills
Installs to: ~/.claude/skills/datamol
Collection: One of 25 skills cataloged from this repository
Category: Data — 668 skills

What Datamol does

Datamol provides a Pythonic wrapper around RDKit for molecular cheminformatics, including SMILES parsing, standardization, descriptors, fingerprints, clustering, and 3D conformers. Use it for drug discovery and molecular data workflows.

Datamol is cataloged under Data on DirSkills. Datamol comes from a repository tagged agent-skills, ai-scientist, bioinformatics, chemoinformatics and claude.

Documentation

README

Excerpt

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.

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+).

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Datamol

What else does K-Dense-AI publish alongside Datamol?
Datamol is one of 25 skills that DirSkills catalogs from K-Dense-AI/scientific-agent-skills, the repository it ships in. Its siblings there include Adaptyv Bio Foundry API, Aeon and Analytical Method Validation. Each one is a separate skill with its own page in this directory, installs the same way Datamol does, and is maintained by K-Dense-AI in that same repository. The rest of the collection is listed on the K-Dense-AI/scientific-agent-skills page.
How does Datamol compare to other Data skills?
Datamol ranks #32 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Datamol against them. Open each page to compare what they document and how they install.