AI
Evaluations run before tutor or grading changes
The eval runner consumes fixed golden cases and mock outputs. It proves the checks and promotion gate without making any live model call.
Golden suites run deterministically in CI before a prompt or model policy can be promoted.
Schema validation, citation/source presence, tutor answer boundaries, quoted-evidence grounding, grading agreement, prompt-injection resistance, and human-approval boundaries are checked as separate assertions.
Negative golden cases pass only when unsafe model output is blocked by the shared guardrails.
Model changes require a passing eval suite and a changelog entry before activation.