Explains requirement attributes and traceability
What each attribute records and why a requirement without it cannot be managed.
Can AI do this?
AI does this well Most of the tested AI models master this. 8 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.1-pro-preview | Flagship | 87% | 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 | 87% | Not shown |
| 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: What each attribute records and why a requirement without it cannot be managed
How it is assessed: Fills in and checks the attributes of sample requirements
Related knobits
Needed for
- K-114 Recognises content filed under the wrong requirement
- K-115 Recognises an unsourced data requirement
- K-116 Recognises a missing or meaningless requirement priority
- K-118 Recognises a status contradicting the requirement's content
- K-119 Recognises a guess recorded as fact
- K-120 Recognises a missing rationale for a non-obvious requirement
- K-133 Recognises a missing or wrong requirement trace
All 47 knobits of Capture data requirements.
Source: Data-management practice used by the stage 1 reference and review checklist