Matminer Composition Featurization
SkillAI & modelsUse this skill to compute deterministic stoichiometry-style composition features for a short list of formulas with matminer.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Matminer Composition Featurization skill
About this capability
A framework for discovering, compiling, and validating reusable skills for scientific agents.
What this skill tells your AI
The instructions your AI receives, as published by ma-compbio-lab/skillfoundry in skills/materials-science-and-engineering/matminer-composition-featurization/SKILL.md and read by ahel’s review.
Use this skill to compute deterministic stoichiometry-style composition features for a short list of formulas with matminer.
What it does
- Parses one or more formulas with
pymatgen. - Computes
matminerstoichiometry features for each composition. - Returns compact JSON with reduced formulas, simple stoichiometry norms, and top element fractions.
When to use it
- You need a first runnable materials-informatics starter in this repository.
- You want a light composition-featurization template before moving to heavier property-prediction workflows.
Example
slurm/envs/materials/bin/python skills/materials-science-and-engineering/matminer-composition-featurization/scripts/run_matminer_composition_features.py \
--formula Fe2O3 \
--formula LiFePO4 \
--out scratch/materials/matminer_features.json
Verification
- Skill-local tests:
python3 -m unittest discover -s skills/materials-science-and-engineering/matminer-composition-featurization/tests -p 'test_*.py' - Repository smoke:
python3 -m unittest tests.smoke.test_frontier_domain_skills -v
Signals
- GitHub stars
- 39
- Forks
- 5
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
matminer-composition-featurization- Source
- github.com/ma-compbio-lab/skillfoundry