A better answer. Or just a different one?

Run your changes against the same real examples. See what improved, what broke, and which answers still need work before you ship.

Change the prompt. Keep the test cases.
SUPPORT QA / 24 CASES
01 / COMPARE ON THE SAME EVIDENCEBASELINE → CANDIDATE
Same 24
questions.

Real examples.
Expected answers.
One frozen dataset.

Original prompt

18/ 24 pass

Updated prompt

23/ 24 pass
5 improved / 0 regressed / 1 still needs workEVERY SQUARE IS A CASE
Look beyond the score.

Test question

Can I return my order after 45 days?

Improved

Before

Yes! You can return your order within 60 days.

After

The return window is 30 days, so an order delivered 45 days ago is outside the policy. [1]

Interactive explanation · illustrative data, not a live application run

THE QUESTION THAT MATTERS

Did my change actually make things better?

01The same cases.

02A clear definition of good.

03A result you can defend.

DATASETS02

Keep the mistakes you never want to repeat.

Turn a useful trace into a test case. Save the input, relevant context, and expected behavior in a dataset you can run against future changes.

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Start from real evidence

Promote a production trace or span into a case with provenance, or create and import cases directly.

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Define the expectation

Keep the observed output separate from the expected answer. Add metadata that explains why the case matters.

Explore datasets

A production mistake becomes a test

Input

Can I return my order after 45 days?

Expected behavior

Explain that the 30-day return window has passed. Cite the returns policy.

Output diff

Expected output
The return window is 30 days, so an order delivered 45 days ago is outside the policy. [1]
Actual output
The return window is 60 days, so an order delivered 45 days ago is within the policy.

SCORERS03

Tell the test what “good” means.

Check an exact value with code, ask an LLM judge to apply a rubric, or combine several checks. Each result keeps the score and its reason.

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Choose the right check

Use JavaScript, Python, LLM, or library scorers for the quality question you need to answer.

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Test the scorer itself

Preview a rule against known good and bad examples. An execution error remains an error, not a zero score.

Explore scorers
Model
Datool Scorer Model
Rubric
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Choice scores
Pass
1
Fail
0

REVIEWS & HUMAN SCORES04

Some answers need a human eye.

An answer can pass a code check and still be unhelpful. Give reviewers the original evidence and shared criteria to judge correctness, tone, and usefulness.

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Build a review queue

Select useful traces and organize them into a session with instructions and assigned reviewers.

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Review in context

Read inputs, outputs, and spans in the inspector. Annotate the exact passages that need attention.

Explore reviews

A shared rubric, not a gut feeling

“The answer is accurate, but it could explain the customer’s next option.”
Correctness Correct
Helpfulness
12345
Reviewed byJL Jamie Lee
Keep the judgment beside the original evidence.

THE EVALUATE TOOLKIT

A repeatable answer to “did it get better?”

START WITH ONE REQUEST

Give your next change something to prove.

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