Recognises a modelling standard named but not chosen
A convention left open, or the plan and model-config.yaml disagreeing.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 1 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 89% | Not shown |
| gemini-3.5-flash-lite | Low cost | 92% | Mastered |
| gpt-6-luna | Low cost | 90% | Not shown |
| claude-haiku-5-5 | Low cost | 89% | 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: The open or contradicting convention and the one value to choose
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: naming: "iso-11179 or snake-case (to be decided)" Acceptable: naming: model-config.yaml#conventions.naming = iso-11179
Also known as: Standard named but not chosen
Related knobits
Builds on
- K-921 Explains data modelling and design standards
- K-919 Explains naming conventions for data model objects
Usually followed by
All 10 knobits of Plan the modelling and set its standards.
Source: Review checklist 00-planning-standards, row 2 (DMBOK §6; 11179-5)