Grading rubric for an agent's answers

Score outputs consistently, by hand or with a second model, and know when quality drops.

Any agent where 'it seems fine' is currently the quality process.evaluationqualityagents
ChatGPT Claude
Build a grading rubric for my agent's outputs, usable by a person or by a second model.

What the agent does: <one paragraph>
What a great answer looks like: <describe, or paste 2 examples>
What a bad answer looks like: <describe, or paste 2 examples>
What must never appear in an answer: <list>
Who judges quality today and how: <honest>

Produce:
1. Five to seven criteria, each with a name, a one-line definition, and what a 1, 3 and 5 look like. Criteria must be observable in the text, not vibes (e.g. "cites a source for every factual claim", not "trustworthy").
2. Hard fails: conditions that make the whole answer a 0 regardless of other scores.
3. A weighting, with one line of reasoning per weight.
4. A grader prompt for a second model: the rubric, the instruction to quote evidence for each score, and a strict JSON output with scores, quotes and an overall pass/fail.
5. Grade my two good and two bad examples with the rubric. If the rubric doesn't separate them clearly, revise it and show the revision.
6. The weekly report: which three numbers I look at, and the threshold that triggers a prompt review.

Replace every <placeholder> with your own details before you send it.

How to use it

  1. 1Grade 20 real outputs by hand with the rubric before automating it. You'll fix the rubric.
  2. 2Use a different model as the grader than the one being graded.
  3. 3Track the score weekly. A drop after a prompt change is the whole point.

Reviewed 2026-09-20

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