Computes stewardship queue capacity from the statistics
Arrivals per week against stewards times resolutions per steward, with the backlog trend and the change needed
Can AI do this?
Not settled yet The benchmark tested this, but the models' answers do not settle yet whether they master it. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 81% | Not shown |
| gemini-3.5-flash-lite | Low cost | 83% | Not shown |
| gpt-6-luna | Low cost | 82% | Not shown |
| claude-haiku-5-5 | Low cost | 83% | 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: Arrivals per week against stewards times resolutions per steward, with the backlog trend and the change needed
How it is assessed: The capacity figure follows from the given statistics
Related knobits
Builds on
All 13 knobits of Run the stewardship workflow and measure MDM.
Source: Graded on its own by rmd-stewardship-metrics