> ## Documentation Index
> Fetch the complete documentation index at: https://developers.agentx.so/llms.txt
> Use this file to discover all available pages before exploring further.

# Get Test Cases

> Read the dataset's questions to drive a CI evaluation

The test cases a CI run executes are the dataset's own `questions` array - there is no separate
test-case endpoint. Fetch the dataset, iterate `questions`, run your agent on each
`main_question.query`, and submit each answer with the case's array position as
`questionIndex`.

This is the same endpoint as [Get Dataset](/api-reference/custom-eval/get-dataset); this page
covers the CI angle.

## Authentication

<ParamField header="x-api-key" type="string" required>
  Project API key.
</ParamField>

## Path Parameters

<ParamField path="datasetId" type="string" required>
  Dataset `_id`.
</ParamField>

## Using the response in CI

For each element of `questions` (0-based index `i`):

* `main_question.query` is the input to pose to your agent.
* Submit the answer with `questionIndex: i` (and `runNumber` 1 through `numberOfRequests` when
  repeating cases for consistency).
* `main_question.splits`, when present, tags the case's named subsets - a run created with
  `"split": "smoke"` should execute only cases tagged `"smoke"`, keeping their original
  indexes.
* `expectedResults`, `expectedTrajectory`, and the other grading fields are read server-side
  by the judge and scorers; your harness doesn't need them (though `expectedResults` is useful
  for local debugging).

## Errors

| Status | Body                               | Meaning                                |
| ------ | ---------------------------------- | -------------------------------------- |
| `404`  | `{ "error": "Dataset not found" }` | No dataset with this id in the project |

<RequestExample>
  ```bash cURL theme={null}
  curl "http://localhost:4700/api/v1/custom-agent-evaluations/datasets/dS4tG7hNb2VxZ8kQ5wMyA" \
    -H "x-api-key: agtx_local_0f3c9a17d2b84e6a5c01b9f4e7d8a2c6431b5f97a0e2d4c8"
  ```

  ```bash Extract just the queries (jq) theme={null}
  curl -s "http://localhost:4700/api/v1/custom-agent-evaluations/datasets/dS4tG7hNb2VxZ8kQ5wMyA" \
    -H "x-api-key: $AGENTX_API_KEY" \
    | jq -r '.questions[].main_question.query'
  ```
</RequestExample>

<ResponseExample>
  ```json 200 OK theme={null}
  {
    "_id": "dS4tG7hNb2VxZ8kQ5wMyA",
    "name": "Customer Support Q3 2026",
    "numberOfRequests": 1,
    "questions": [
      { "main_question": { "query": "How do I reset my password?", "expectedResults": "Click Forgot Password on the login screen.", "splits": ["smoke"] } },
      { "main_question": { "query": "What payment methods do you accept?" } },
      { "main_question": { "query": "How long does shipping take?" } }
    ],
    "status": "published",
    "createdAt": "2026-08-27T10:00:00.000Z"
  }
  ```
</ResponseExample>