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GET
/
v1
/
agent-testing
/
runs
/
{id}
Get Test Run
curl --request GET \
  --url https://api.bland.ai/v1/agent-testing/runs/{id} \
  --header 'authorization: <authorization>'
{
  "id": "a3f1b2c4-5d6e-7f8a-9b0c-1d2e3f4a5b6c",
  "scenario_id": "1a2b3c4d-5e6f-7a8b-9c0d-1e2f3a4b5c6d",
  "pathway_id": "b1693602-c05e-4b5c-b187-d0189a42aebf",
  "persona_id": "c2d3e4f5-6a7b-8c9d-0e1f-2a3b4c5d6e7f",
  "batch_id": null,
  "status": "PASSED",
  "chat_history": [
    {
      "role": "assistant",
      "content": "Hello! Thanks for calling Acme Dental. How can I help you today?"
    },
    {
      "role": "user",
      "content": "Hi, I'd like to book a cleaning appointment for next week."
    },
    {
      "role": "assistant",
      "content": "I'd be happy to help you schedule a cleaning. Let me check our availability. Do you have a preferred day next week?"
    },
    {
      "role": "user",
      "content": "Tuesday or Wednesday would work best for me."
    },
    {
      "role": "assistant",
      "content": "We have openings on Tuesday at 10 AM and Wednesday at 2 PM. Which works better for you?"
    },
    {
      "role": "user",
      "content": "Tuesday at 10 AM sounds perfect."
    },
    {
      "role": "assistant",
      "content": "Great, I've booked your cleaning appointment for Tuesday at 10 AM. You'll receive a confirmation text shortly. Is there anything else I can help with?"
    },
    {
      "role": "user",
      "content": "No, that's all. Thank you!"
    },
    {
      "role": "assistant",
      "content": "You're welcome! We'll see you Tuesday. Have a great day!"
    }
  ],
  "variables_extracted": {
    "appointment_date": "2026-04-21",
    "appointment_time": "10:00",
    "service_type": "cleaning"
  },
  "nodes_visited": [
    "greeting",
    "identify_intent",
    "check_availability",
    "offer_slots",
    "confirm_booking",
    "closing"
  ],
  "current_node_id": "closing",
  "turn_count": 9,
  "duration_ms": 14320,
  "overall_score": 0.92,
  "bland_tone_score": {
    "naturalness": 0.95,
    "conciseness": 0.88,
    "empathy": 0.91,
    "flow_preservation": 0.93,
    "back_channeling": 0.85,
    "topic_transitions": 0.90,
    "overall_tone_score": 0.91,
    "issues": [],
    "examples": [
      {
        "turn": 3,
        "category": "empathy",
        "text": "I'd be happy to help you schedule a cleaning.",
        "sentiment": "positive"
      }
    ]
  },
  "assertion_results": [
    {
      "assertion_id": "d4e5f6a7-8b9c-0d1e-2f3a-4b5c6d7e8f9a",
      "type": "contains",
      "target": "transcript",
      "expected": "appointment",
      "passed": true
    },
    {
      "assertion_id": "e5f6a7b8-9c0d-1e2f-3a4b-5c6d7e8f9a0b",
      "type": "node_visited",
      "target": "nodes_visited",
      "expected": "confirm_booking",
      "passed": true
    },
    {
      "assertion_id": "f6a7b8c9-0d1e-2f3a-4b5c-6d7e8f9a0b1c",
      "type": "variable_equals",
      "target": "variables_extracted",
      "field": "service_type",
      "expected": "cleaning",
      "passed": true
    }
  ],
  "error_message": null,
  "created_at": "2026-04-14T10:30:00.000Z"
}

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.

​
Headers

​
authorization
string
required
Your API key for authentication.

​
Path Parameters

​
id
string
required
The unique identifier of the test run.

​
Response

​
id
string
The unique identifier for the test run.
​
scenario_id
string
The ID of the scenario that was executed.
​
status
string
The current status of the run. One of: PENDING, RUNNING, PASSED, FAILED, ERROR, CANCELLED.
​
chat_history
array of objects
The full conversation history between the simulated persona and the agent. Each entry contains:
  • role - Either user (the persona) or assistant (the agent).
  • content - The text spoken in that turn.
​
variables_extracted
object
Variables that were extracted or set during the test run. Keys are variable names, values are the extracted values.
​
nodes_visited
array of strings
An ordered list of pathway node IDs that were visited during the test run.
​
current_node_id
string
The node ID where the conversation ended.
​
turn_count
integer
The total number of conversational turns in the test run.
​
duration_ms
integer
The total duration of the test run in milliseconds.
​
overall_score
number
A score between 0 and 1 representing how well the agent performed across all assertions and evaluations.
​
bland_tone_score
object
A detailed tone analysis of the agent’s responses. Contains:
  • naturalness - Score (0-1) for how natural the agent sounded.
  • conciseness - Score (0-1) for response brevity and clarity.
  • empathy - Score (0-1) for empathetic responses.
  • flow_preservation - Score (0-1) for maintaining conversation flow.
  • back_channeling - Score (0-1) for appropriate use of acknowledgments.
  • topic_transitions - Score (0-1) for smooth topic changes.
  • overall_tone_score - Aggregate tone score (0-1).
  • issues - Array of identified tone issues.
  • examples - Array of specific examples from the conversation.
​
assertion_results
array of objects
Results for each assertion defined in the scenario. Each entry includes the assertion configuration and whether it passed or failed.
​
error_message
string
If the run status is ERROR, this contains a description of what went wrong. Otherwise null.
​
created_at
string
ISO 8601 timestamp for when the run was created.
{
  "id": "a3f1b2c4-5d6e-7f8a-9b0c-1d2e3f4a5b6c",
  "scenario_id": "1a2b3c4d-5e6f-7a8b-9c0d-1e2f3a4b5c6d",
  "pathway_id": "b1693602-c05e-4b5c-b187-d0189a42aebf",
  "persona_id": "c2d3e4f5-6a7b-8c9d-0e1f-2a3b4c5d6e7f",
  "batch_id": null,
  "status": "PASSED",
  "chat_history": [
    {
      "role": "assistant",
      "content": "Hello! Thanks for calling Acme Dental. How can I help you today?"
    },
    {
      "role": "user",
      "content": "Hi, I'd like to book a cleaning appointment for next week."
    },
    {
      "role": "assistant",
      "content": "I'd be happy to help you schedule a cleaning. Let me check our availability. Do you have a preferred day next week?"
    },
    {
      "role": "user",
      "content": "Tuesday or Wednesday would work best for me."
    },
    {
      "role": "assistant",
      "content": "We have openings on Tuesday at 10 AM and Wednesday at 2 PM. Which works better for you?"
    },
    {
      "role": "user",
      "content": "Tuesday at 10 AM sounds perfect."
    },
    {
      "role": "assistant",
      "content": "Great, I've booked your cleaning appointment for Tuesday at 10 AM. You'll receive a confirmation text shortly. Is there anything else I can help with?"
    },
    {
      "role": "user",
      "content": "No, that's all. Thank you!"
    },
    {
      "role": "assistant",
      "content": "You're welcome! We'll see you Tuesday. Have a great day!"
    }
  ],
  "variables_extracted": {
    "appointment_date": "2026-04-21",
    "appointment_time": "10:00",
    "service_type": "cleaning"
  },
  "nodes_visited": [
    "greeting",
    "identify_intent",
    "check_availability",
    "offer_slots",
    "confirm_booking",
    "closing"
  ],
  "current_node_id": "closing",
  "turn_count": 9,
  "duration_ms": 14320,
  "overall_score": 0.92,
  "bland_tone_score": {
    "naturalness": 0.95,
    "conciseness": 0.88,
    "empathy": 0.91,
    "flow_preservation": 0.93,
    "back_channeling": 0.85,
    "topic_transitions": 0.90,
    "overall_tone_score": 0.91,
    "issues": [],
    "examples": [
      {
        "turn": 3,
        "category": "empathy",
        "text": "I'd be happy to help you schedule a cleaning.",
        "sentiment": "positive"
      }
    ]
  },
  "assertion_results": [
    {
      "assertion_id": "d4e5f6a7-8b9c-0d1e-2f3a-4b5c6d7e8f9a",
      "type": "contains",
      "target": "transcript",
      "expected": "appointment",
      "passed": true
    },
    {
      "assertion_id": "e5f6a7b8-9c0d-1e2f-3a4b-5c6d7e8f9a0b",
      "type": "node_visited",
      "target": "nodes_visited",
      "expected": "confirm_booking",
      "passed": true
    },
    {
      "assertion_id": "f6a7b8c9-0d1e-2f3a-4b5c-6d7e8f9a0b1c",
      "type": "variable_equals",
      "target": "variables_extracted",
      "field": "service_type",
      "expected": "cleaning",
      "passed": true
    }
  ],
  "error_message": null,
  "created_at": "2026-04-14T10:30:00.000Z"
}
Docs for agents: llms.txt