Model-Validation Skill

Purpose

This skill pressure-tests the validation study for an engineer-built medical-imaging model — the common case where a clinical team receives a trained segmentation / classification / detection model from an engineering collaborator and must validate it and write it up. It is the imaging-model specialization of /design-study: where design-study covers general validity and design-ai-benchmarking covers AI-versus-human-expert reader studies, this skill owns the partition, leakage, reproducibility, and metric-selection mechanics that decide whether a reported Dice / AUROC / sensitivity is trustworthy.

It is advisory and deterministic-audit only. It writes decision notes and runs a stdlib gate on the split table; it never builds, trains, or alters the model, and it never replaces MONAI / nnU-Net / TorchIO — those produce the model, this validates and publishes it.