Use Therapeutics Data Commons through the PyTDC Python package for registry discovery, approved dataset access, task-aware splits (scaffold, cold-start, temporal, combination), evaluator metrics, benchmark groups, and bounded molecular-oracle workflows. Use this skill to find which TDC datasets exist for a therapeutic task, load them with a split that does not leak, score predictions with the task's own official metric rather than a generic one, and run benchmark groups reproducibly. Also trigger on PyTDC, Therapeutics Data Commons, tdc.single_pred, tdc.multi_pred, ADMET Benchmark Group, scaff...
At a glance
This skill is for Coding and helps you load drug discovery datasets with appropriate data splits, access therapeutics data commons registry, and evaluate molecular predictions with official metrics.
git clone --depth 1 https://github.com/K-Dense-AI/drug-discovery-agent-skills
cp -r drug-discovery-agent-skills/skills/pytdc ~/.claude/skills/pytdc
PytdcTherapeutics Data Commonsdrug-discoveryMolecular PredictionbenchmarkData Splits
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