Overview
deepchem is an open-source data skill for Claude Code and compatible agents, published by K-Dense-AI. Its author describes it as: “Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best fo…”. The project has 40k stars on GitHub and is available under the MIT license. Add it to your setup with `git clone https://github.com/K-Dense-AI/scientific-agent-skills ~/.claude/skills/deepchem`.
What deepchem does
DeepChem is a comprehensive Python library for applying machine learning to chemistry, materials science, and biology. Enable molecular property prediction, drug discovery, materials design, and biomolecule analysis through specialized neural networks, molecular featurization methods, and pretrained models.
What’s inside
The SKILL.md for deepchem is organised into these sections:
- Overview
- When to Use This Skill
- Core Capabilities
- Example Scripts
- 1. predictsolubility.py
- 2. graphneuralnetwork.py
- 3. transferlearning.py
- Common Patterns and Best Practices
- Pattern 1: Always Use Scaffold Splitting for Molecules
- Pattern 2: Normalize Features and Targets
- Pattern 3: Start Simple, Then Scale
- Pattern 4: Handle Imbalanced Data
Installation
Add deepchem to your agent with:
git clone https://github.com/K-Dense-AI/scientific-agent-skills ~/.claude/skills/deepchemReview a skill’s source before installing it — skills can instruct your agent to run commands. This command comes from the skill’s public repository, which is the source of truth for setup steps. New to skills? Read how to install Claude Code skills.
Supported agents
Neither the skill nor its repository names a specific agent. It uses the SKILL.md format, which several agents can load — check the repository for any agent-specific requirements.
License
deepchem is published under the MIT license.
Strengths
- Clear MIT license — safe to read and adapt within its terms
- Ships in K-Dense-AI/scientific-agent-skills, an established project with 40,410 GitHub stars
- Actively maintained — repository updated in the last 30 days
- Its repository gained 6,589 GitHub stars over the last 13 days
Author
Topics
Frequently asked questions
- What does deepchem do?
- Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.
- How do I install deepchem?
- Run git clone https://github.com/K-Dense-AI/scientific-agent-skills ~/.claude/skills/deepchem in your agent, then reload your skills. Review the source at https://github.com/K-Dense-AI/scientific-agent-skills before installing.
- Is deepchem free to use?
- Yes. deepchem is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Where does deepchem come from?
- deepchem ships inside K-Dense-AI/scientific-agent-skills, a repository that contains 42 catalogued skills in total. The repository's 40,410 GitHub stars apply to that whole collection, not to this skill on its own.