deepchem
deepchem is a Chemistry & materials skill for AI agents, published by K-Dense-AI in the scientific-agent-skills repository on GitHub. Skillspace rates deepchem C (79/100) and it passed the safety scan; a judge model has also reviewed it.
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.
- Grade
- C
- Quality
- 79 / 100
- Safety
- Passed
- GitHub stars
- 44,723
Placed #2 of 6 in the judged category final for Chemistry & materials.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 97 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #2 of 6 in the judged category final for Chemistry & materials.
- Trigger
92 92 - Instructions
92 92 - Specificity
93 93 - Safety
88 88 - Disclosure
90 90 - Maintenance
88 88
Cleanly differentiates itself from adjacent tools and backs its best practices with contrastive good/bad code instead of bare assertions.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Also published in 1 other repo
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