Independent relevance is not a mutually exclusive choice
One tool’s Noul score need not decrease when another tool scores highly. The local top-K policy imposes the actual menu-size constraint.
Inspect the supporting source ↗A research repository evaluating Jev relevance judgments for task-level tool menus using controlled TGB and BFCL protocols.
Independent Noul questions score each tool against shared task evidence; local aggregation and top-K rules produce menu masks for downstream evaluation.
Separates relevance scoring from downstream tool-use success and records model/state/question identities for cache reuse.
Fixed-version documentation and implementation material were inspected on 2026-10-24. No GPU benchmark or live scoring was run. Published sample results and historical service limits were not revalidated as current platform guarantees.
Evaluate task-level tool menus rather than ask Jev to execute a tool.
Material analysed:
One tool’s Noul score need not decrease when another tool scores highly. The local top-K policy imposes the actual menu-size constraint.
Inspect the supporting source ↗client.py hashes model, state and questions, allowing exact request reuse. Prompt changes invalidate that key; the shipped mock is deterministic synthetic output, not model evaluation.
Inspect the supporting source ↗Useful for controlled tool-menu research. Keep build/test splits and compare downstream tool-use results; high relevance scores alone do not demonstrate task completion.
Read the README’s protocol and client.py _key/ask methods. Confirm that changing a question changes the cache identity and that JEV_MOCK records model=MOCK rather than real usage.