alterlab-deepchem

alterlab-deepchem is a Chemistry & materials skill for AI agents, published by AlterLab-IEU in the AlterLab-Academic-Skills repository on GitHub. Skillspace rates alterlab-deepchem B (83/100) and it passed the safety scan; the rating is based on static analysis only.

Runs molecular machine learning with DeepChem — diverse featurizers, pre-built MoleculeNet benchmark datasets, and pre-trained models (ChemBERTa, GROVER) for property prediction (ADMET, toxicity, solubility) via traditional ML or graph neural networks. Use when running end-to-end molecular ML experiments that need MoleculeNet benchmarks, scaffold splitting, or ready-made models with minimal setup; for building custom PyTorch graph architectures prefer alterlab-torchdrug, and for standalone molecule-to-feature-vector generation prefer alterlab-molfeat. Part of the AlterLab Academic Skills suite.

Grade
B
Quality
83 / 100
Safety
Passed
GitHub stars
43

Unproven: rated by static analysis only, not yet compared head-to-head.

Not launch-quality. It is graded B 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
100 / 100
Maturity
Packaged: licensed, with a version or references
Security scan
Low-risk patterns
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

What the scanner flagged

  • over-broad allowed-tools ('*')

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • 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

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