T3-R4 in five minutes
Ten to fifty checks beat one demo.
Each item has an input, an expected property, and a source.
The property can be 'refuses' or 'cites this note'.
Lab 03 is a local example with a fixed file.
Do not add items after you see the score and pretend the set was always that.
Write the set before you tune. If you add a case because the model failed it, mark that case as new so the old score stays comparable.
Sources and go deeper
- Python 3 tutorial vendor last checked 2026-10
- NIST AI Risk Management Framework spec last checked 2026-10
- Large language model — Wikipedia wikipedia last checked 2026-10