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Authoring eval cases

Eval cases require care: the question, the answer, the rationale.

Yash ShahMarch 5, 20262 min read

Authoring eval cases is harder than it looks. The team's first dozen cases probably need rework. The patterns become clear after a few hundred.

The question-and-answer discipline

For each case:

  • The input. Specific, realistic, well-formed.
  • The expected output. What "good" looks like.
  • The rationale. Why this case matters.
  • The category. Happy path, edge, adversarial.
  • The difficulty. Easy, medium, hard.

The discipline: write each piece consciously. The rationale matters most.

Reviewer ritual

New eval cases get reviewed:

  • Is the input realistic?
  • Is the expected output unambiguous?
  • Is the rationale meaningful?
  • Does this case belong in the set, or is it redundant?

A real case-study

A team authoring cases for a tone-classification feature:

case_id: 042
input: "I'd appreciate a quick update on my order"
expected_tone: "polite"
rationale: "Soft request without demand language; tests recognition of polite tone in conversational language"
category: "happy_path"
difficulty: "easy"

Compared to a poorly-authored case:

case_id: 043
input: "Where is my stuff?"
expected_tone: "neutral"

The second is ambiguous. Different annotators might call it "neutral" or "frustrated." Without context, the case is noise.

Trade-offs

Authoring is slow:

  • 5-10 minutes per case for the rationale-rich format.
  • 30 seconds for the bare-minimum format.

The slow format produces cases that endure. The fast format produces noise.

What we won't ship

Cases without rationale.

Cases with ambiguous expected outputs.

Cases that are duplicates of existing ones.

Cases the author can't justify.

Close

Authoring eval cases is the discipline of writing each one consciously. The input. The expected output. The rationale. Skip any and the case becomes noise. Include all three and the case earns its place.

Related reading


We build AI-enabled software and help businesses put AI to work. If you're tightening eval-case authoring, we'd love to hear about it. Get in touch.

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EvalsAI EngineeringEngineeringOutput TestingAuthoring
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