byalterlab-ieu· 90 skills
Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel batch processing, returning native rdkit.Chem.Mol objects. Use when running standard cheminformatics pipelines on molecule tables with minimal boilerplate; for low-level control, custom sanitization, or specialized algorithms prefer alterlab-rdkit. Part of the AlterLab Academic Skills suite.
$npx -y skills add alterlab-ieu/alterlab-academic-skills --skill alterlab-datamolInstalls into the current project.
Run `npx skills use "https://github.com/alterlab-ieu/alterlab-academic-skills" --skill "alterlab-ieu/alterlab-academic-skills/alterlab-datamol"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/alterlab-ieu/alterlab-academic-skills" that are relevant to the current task. Run `npx skills add "https://github.com/alterlab-ieu/alterlab-academic-skills"` and select the relevant skills, then follow their instructions.