Dataset schema validation: fail before training

Structured output lessons taught you to validate model responses. Dataset validation is the same habit aimed at rows.

Before a model trains, every row should answer basic questions: are required fields present, are types sane, are labels allowed, and did an upstream agent rename a column?

A schema is not bureaucracy. It is the cheapest place to catch a bad dataset, before the bug becomes a misleading metric.