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Where this fits: Part of Refine. Expected output turns a dataset of real traces into a test set with a known-good answer for regression testing.
Expected output is the correct or desired answer for a dataset row. It lets a test compare your agent’s actual output against a known-good result, rather than only checking the output in isolation. Expected output is optional, since many evaluations check a response on its own merits, but it is what makes a row a precise regression case.

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Add expected output to a row

1

Open the row

In a dataset, open a row to view its input, output, and fields.
2

Fill in the expected output

Add the correct answer in the Expected output field. A row with no expected output shows an Add expected output prompt, so it is easy to see which rows still need one.
A dataset row detail view showing the Expected output field filled in alongside the input and output

A dataset row with its expected output filled in, ready to be used as a regression case.

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Where the expected answer comes from

When you build a dataset from a failing signal, the agent’s actual output was wrong, which is why the signal exists. The expected output is the response the agent should have produced. Common sources:
  • the correct answer a human reviewer would give
  • the behaviour described in the signal or in an annotation
  • a corrected version of the original output

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Add it programmatically

You can also set expected output (or any other cell) over the API, the SDKs, or an MCP agent — handy for filling in answers in bulk or straight from your coding agent after building a dataset. See Edit row contents.

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