datarobot-predictions

# DataRobot Predictions Skill This skill provides comprehensive guidance for working with DataRobot predictions, including real-time predictions, batch scoring, and generating prediction datasets. ## Quick Start **Most common use case**: Generate predictions for a deployment 1. **Get deployment features**: `get_deployment_features(deployment_id)` to understand required columns 2. **Generate template**: `generate_prediction_data_template(deployment_id, n_rows)` to create CSV structure 3. **Make predictions**: Use `deployment.predict_batch(...)` (works for both single-row “real-time” and batch scoring) **Example**: "Generate a prediction dataset template for deployment abc123 with 10 rows" **To also explain predictions**: pass `--max-explanations N` to `make_prediction.py` (or the `max_explanations=N` kwarg in code). See [Prediction Explanations](#prediction-explanations) below. ## When to use this skill Use this skill when you need to: - Make predictions from deployed DataRobot models - Explain individual predictions from a deployment (SHAP or XEMP, per-row) - Generate prediction dataset templates - Validate prediction data before scoring - Understand deployment feature requirements - Perform batch predictions on large datasets - Get sample training data to understand expected formats > For post-hoc explanations against a **training project / leaderboard model** (not a deployment), > use the `datarobot-model-explainability` skill instead. This skill covers deployment-...