Explains verifiable requirement statements
A requirement a test can pass or fail, with measures, units, thresholds and references stated.
Can AI do this?
AI does this well Most of the tested AI models master this. 9 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.1-pro-preview | Flagship | 88% | Not shown |
| gpt-6-astra | Flagship | 100% | Mastered |
| claude-fable-5-1 | Flagship | 100% | Mastered |
| gemini-3.8-flash | Mid tier | 100% | Mastered |
| gpt-6.1-sol | Mid tier | 100% | Mastered |
| claude-sonnet-5-5 | Mid tier | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 100% | Mastered |
| gpt-6-luna | Low cost | 100% | Mastered |
| claude-haiku-5-5 | Low cost | 100% | Mastered |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: A requirement a test can pass or fail, with measures, units, thresholds and references stated
How it is assessed: Rewrites sample statements so a test could fail them
Related knobits
Needed for
- K-105 Recognises untestable wording in a data requirement
- K-106 Recognises an unverifiable data requirement
- K-109 Recognises a measure stated without unit or basis
All 47 knobits of Capture data requirements.
Source: Data-management practice used by the stage 1 reference and review checklist