Agens deepchem

skill_id: deepchem name: deepchem description: 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. version: 1.0.0 author: K-Dense Inc. license: MIT license tags:

• scientific-agent-skills
• deepchem tools: [] permissions: network: false filesystem: false shell: false agents:
• bio_code_agent enabled: true source: scientific-agent-skills entrypoint: entry.py readme: README.md input_schema: {} output_schema: type: object metadata: upstream_repo: K-Dense-AI/scientific-agent-skills upstream_skill: deepchem upstream_path: scientific-skills/deepchem/SKILL.md upstream_frontmatter: name: deepchem description: 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. license: MIT license metadata: skill-author: K-Dense Inc.