datamol
datamol is a Chemistry & materials skill for AI agents, published by aipoch in the medical-research-skills repository on GitHub. Skillspace rates datamol C (78/100) and it passed the safety scan; a judge model has also reviewed it.
A Pythonic wrapper around RDKit with simplified interfaces and sensible defaults. Preferred for standard drug discovery workflows including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformer generation, and parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
- Grade
- C
- Quality
- 78 / 100
- Safety
- Passed
- GitHub stars
- 1,449
Placed #3 of 3 when judged against its near-duplicates in Chemistry & materials.
Not launch-quality. It is graded C with a clean safety verdict, but our quality filters exclude it: it is a near-duplicate variant of another skill. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 2 collections
- Scope
- Vendor-specific: built around one product. Usage of datamol, a public RDKit wrapper library
Judge review
Placed #3 of 3 when judged against its near-duplicates in Chemistry & materials.
- Trigger
76 76 - Instructions
45 45 - Specificity
55 55 - Safety
85 85 - Disclosure
35 35 - Maintenance
30 30
Genuine datamol content is buried under generic auto-generated boilerplate ('validate_skill.py' scaffolding) that has nothing to do with cheminformatics.
Not checked yet
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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