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name: dglgo-cli description: "Use DGL-Go CLI workflows for generating configs, running recipes, training from YAML, exporting scripts, and applying checkpoints." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

DGL-Go CLI

Use this sub-skill when the task asks to run DGL-Go, generate or repair a DGL-Go YAML file, list or copy recipes, train from a YAML config, export a runnable script, or apply a saved DGL-Go checkpoint to inference data.

Fast Routing

• For command syntax, flags, and copy-paste examples, read CLI reference.
• For YAML keys, pipeline modes, recipes, custom CSV data, and checkpoint fields, read configuration.
• For end-to-end configure/train/export/apply flows, read workflows.
• For install, dependency, dataset, checkpoint, and schema failures, read troubleshooting.
• To lint a config without importing DGL-Go or starting training, run python scripts/dglgo_config_linter.py path/to/cfg.yaml.

Boundaries

• Route low-level graph construction, heterographs, batching, and graph serialization to graph-apis.
• Route custom CSV graph layout details and DGL dataset implementation details to datasets-and-io.
• Route GNN module internals, exported script edits, and model customization to message-passing-training.
• Route multi-machine or distributed launch tasks to distributed-tools.

Safety Notes

DGL-Go training and apply commands may download datasets, load checkpoints, import optional packages such as OGB or RDKit, and execute generated Python. Prefer dgl export --cfg ... --output ... for reviewable code before long or unfamiliar runs, and use the bundled linter for safe preflight checks.