{
  "id": "scientific/deepchem",
  "version": "1.0.0",
  "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.",
  "domain": "scientific",
  "source": "external",
  "tools": [],
  "exitStates": [
    "success",
    "failure"
  ],
  "inputSchema": {},
  "outputSchema": {},
  "temperature": 0,
  "tags": [
    "scientific",
    "imported",
    "community"
  ],
  "platforms": {
    "claude": {
      "license": "MIT license",
      "triggers": [
        "help with deepchem",
        "data analysis"
      ]
    },
    "cursor": {},
    "skeneflow": {}
  }
}
