Aglet

Prioritize Grounding Cases for Agent Evaluation

Grounding evaluation should spend attention where a polished answer could cause the most confusion or harm. Prioritize unsupported specificity, conflicting context, and no-answer situations over harmless phrasing differences. Compare case design effort with the decision risk before allocating review time.

Decide where the work belongs

  1. Rank claim consequence

    Describe what could happen if each unsupported claim is accepted: a wrong decision, missed limitation, false confidence, or incorrect action. Give weight to claims that sound precise and to contexts where readers cannot easily verify them.

  2. Compare context slices

    Review short, long, noisy, conflicting, stale, and incomplete context cases. Identify which slices expose retrieval or answer behavior. Keep omission and contradiction separate because a concise answer can be faithful while incomplete for the request.

  3. Choose a grounding queue

    Select cases, claim rules, evaluator owner, and review date. Defer low-consequence wording variations with a trigger. If context provenance is weak, prioritize fixing the evidence record before comparing answers against sourced claims.

What to carry forward

The priority output is a grounding queue tied to claim consequence, context difficulty, user reliance, and evidence quality. Start where unsupported detail could change a decision. Keep lower-risk style issues outside the grounding score until the evidence boundary is stable.

Technical background: Google DeepMind evaluation research.

Keep the decision with the work.

Use a Work Item in Aglet to record the problem, the evidence you have, and the next decision. Add an owner and priority, then keep updates in the discussion so the next person can follow the reasoning.

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