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

# Get Node Test Run

> Retrieve a node test run.

### Path

**id** `string` *required*

The ID of the node test run to retrieve.

### Headers

**authorization** `string` *required*

Your API key for authentication.

### Response

**data.id** `string`

Unique identifier for the node test run.

**data.org\_id** `string`

Organization ID that owns this node test run.

**data.created\_at** `string`

ISO timestamp when the node test run was created.

**data.finished\_at** `string`

ISO timestamp when the node test run finished.

**data.status** `string`

Current status of the node test run. Possible values are `"COMPLETED"`, `"PENDING"`, `"CANCELLED"`, and `"ERROR"`.

**data.pathway\_id** `string`

Identifier of the pathway this node belongs to.

**data.node\_id** `string`

Identifier of the node that was tested within the pathway.

**data.input** `object`

Input configuration used for this node test run.

**data.input.prompt** `string`

The instruction or system prompt used when testing the node.

**data.input.conversations** `array`

Array of conversation references used as context for the node test.

**data.input.conversations\[].id** `string`

Unique identifier of a conversation used in the test.

**data.input.conversations\[].type** `string`

The type of conversation (for example, `"call"`).

**data.result** `array`

Array of result objects, one per evaluated conversation.

**data.result\[].conversation\_id** `string`

ID of the conversation this result corresponds to.

**data.result\[].total\_generations** `number`

Total number of generations produced for this conversation during the test run. For example, if I invoke the test with 5 permutations, then this value will be 6, since we need to generate 5 simulations for the permutations and one generation for the original user messages.

**data.result\[].data** `array`

Array of generation batches for this conversation.

**data.result\[].data\[].is\_original** `boolean`

If true, then this result is the original user and agent interaction on the node.

**data.result\[].data\[].is\_permutation** `boolean`

If true, then this result is a generation using a permutation/variant of the original user inputs.

**data.result\[].data\[].output** `array`

Ordered list of message turns (user/assistant) in this generated interaction.

**data.result\[].data\[].output\[].role** `string`

Role of the message author (`"user"` or `"assistant"`).

**data.result\[].data\[].output\[].node\_id** `string`

Node identifier associated with this message turn.

**data.result\[].data\[].output\[].content** `string`

Text content of the message.

**data.result\[].generating\_new\_prompt** `boolean`

An indicator to show if the system is in the process of simulating the agent response with the new prompt and original user inputs.

**data.result\[].generating\_permutations** `boolean`

An indicator to show if the system is in the process of simulating the agent response with the new prompt and user permutations.

```json Response theme={null}
{
  "data": {
    "id": "727a85f1-1959-4ec1-95a4-248a2eecf1ae",
    "org_id": "99a0d526-6910-4f31-92b8-72834d0827fb",
    "created_at": "2025-11-17T14:47:40.174Z",
    "finished_at": "2025-11-17T14:48:11.399Z",
    "status": "COMPLETED",
    "pathway_id": "05f4b269-e79a-4825-b4cd-7778f782bfad",
    "node_id": "a7bbd409-504b-4ba3-a9d1-12f6bc270f58",
    "input": {
      "prompt": "Tell the user how cool they are and also what they think of the month of December",
      "conversations": [
        {
          "id": "b7d1eab7-f9a2-4e4d-b3ac-4e744cf93d2b",
          "type": "call"
        },
        {
          "id": "f9b44639-4de1-48d9-97ed-08b7fcb6eb1c",
          "type": "call"
        },
        {
          "id": "8c361b43-efa2-49e2-84a2-60ede375161b",
          "type": "call"
        },
        {
          "id": "a915cdce-fd3e-4f9f-b0bd-b5f6ee03ef1f",
          "type": "call"
        }
      ]
    },
    "result": [
      {
        "conversation_id": "b7d1eab7-f9a2-4e4d-b3ac-4e744cf93d2b",
        "data": [
          {
            "output": [
              {
                "role": "user",
                "node_id": "4f74e9a9-6d06-4756-8379-4d06220a4bda",
                "content": "I work at a company that makes boats. I'm a boat builder."
              },
              {
                "role": "assistant",
                "node_id": "a7bbd409-504b-4ba3-a9d1-12f6bc270f58",
                "content": "Gotcha. Okay, so, uh, what would you say are your biggest strengths?"
              }
            ],
            "is_original": true,
            "is_permutation": false
          },
          {
            "output": [
              {
                "role": "user",
                "nodeId": "4f74e9a9-6d06-4756-8379-4d06220a4bda",
                "content": "I work at a company that makes boats. I'm a boat builder."
              },
              {
                "role": "assistant",
                "nodeId": "a7bbd409-504b-4ba3-a9d1-12f6bc270f58",
                "content": "Wow, that sounds like a really cool job. That's pretty unique. You must have some interesting stories. Anyways, what would you say are your biggest strengths?"
              }
            ],
            "is_original": false,
            "is_permutation": false
          }
        ],
        "total_generations": 1,
        "generating_new_prompt": false,
        "generating_permutations": false,
      }
      // ...
    ]
  },
  "errors": null
}
```

***

Docs for agents: [llms.txt](https://docs.bland.ai/llms.txt)


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