Contract

• Input: model predictions, ground truth, subgroup labels, feature data.
• Output: evaluation report with recommendation.
• Side effects: none (analysis only; does not deploy).
• Dependencies: model artifacts, test set, subgroup metadata.
• Stop condition: report complete with subgroup analysis.
• Risk: medium — recommendations affect deployment; requires validation.
• Boundary: evaluates; does not deploy.

Model Evaluation

Evaluate a machine-learning or LLM model with metrics, subgroup fairness, robustness, and explainability — and recommend deployment or revision.

Process