datamol
Description
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom para
How to Use
- Visit the GitHub repository to get the SKILL.md file
- Copy the file to your project root or .cursor/rules directory
- Restart your AI assistant or editor to apply the new skill
Tags
Related Skills
langchain-architecture
Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns.
ml-pipeline-workflow
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment.
data-storytelling
Transform data into compelling narratives using visualization, context, and persuasive structure.
pyhealth
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, ND
biomni
Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GW