Explains consistency within a requirements register
No two requirements say the same thing or contradict each other.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 0 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 94% | Not shown |
| gemini-3.1-pro-preview | Flagship | 87% | Not shown |
| gpt-6-astra | Flagship | 89% | Not shown |
| claude-fable-5-1 | Flagship | 88% | Not shown |
| gemini-3.8-flash | Mid tier | 88% | Not shown |
| gpt-6.1-sol | Mid tier | 87% | Not shown |
| claude-sonnet-5-5 | Mid tier | 87% | Not shown |
| gemini-3.5-flash-lite | Low cost | 89% | Not shown |
| gpt-6-luna | Low cost | 87% | Not shown |
| claude-haiku-5-5 | Low cost | 87% | Not shown |
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: No two requirements say the same thing or contradict each other
How it is assessed: Finds duplicates, paraphrases and conflicts in a sample register
Related knobits
Needed for
- K-121 Recognises duplicate data requirements
- K-122 Recognises paraphrased data requirements
- K-123 Recognises conflicting data requirements
All 47 knobits of Capture data requirements.
Source: Data-management practice used by the stage 1 reference and review checklist