Retrieve AI Agent Log Details

Before You Begin

🔗 Use the GraphQL Playground to execute the queries in this guide.

Prerequisites

1. Authentication: Use a Service Account token (Personal Access Tokens are deprecated).
2. Permissions: You must be admin of the pipe/table.
3. Feature Toggle: The organization must have AI Agents feature enabled via toggle.
4. Log UUID: Identify the execution log UUID to retrieve details from.

Step 1: Find Your Log UUID

See our Get resource IDs page for how to find the pipe UUID.

Via GraphQL Query

• Use the aiAgentLogsByRepo query to list logs and find the UUID:

{
  aiAgentLogsByRepo(repoUuid: "pipe-uuid-123") {
    edges {
      node {
        uuid
        agentName
        status
        createdAt
      }
    }
  }
}

Step 2: Query AI Agent Log Details

Use the aiAgentLogDetails query to retrieve detailed information about a specific AI agent behavior execution log.

{
  aiAgentLogDetails(uuid: "log-uuid-123") {
    uuid
    agentUuid
    agentName
    automation {
      id
      name
    }
    cardId
    cardTitle
    status
    createdAt
    finishedAt
    executionTime
    tracingNodes {
      nodeName
      status
      message
    }
  }
}

Key Fields Explained

• uuid: Log unique identifier.
• agentUuid: UUID of the agent that executed.
• agentName: Name of the agent.
• automation: Automation that triggered the AI agent behavior execution.
• cardId: ID of the card/record involved (if any).
• cardTitle: Title of the card/record involved (if any).
• status: Status of the execution (processing, success, failed).
• createdAt: When the log was created.
• finishedAt: When the execution success (null if still processing).
• executionTime: Execution time in seconds.
• tracingNodes: Tracing nodes of the AI agent behavior execution, showing the execution flow and any errors.

Status Values

The status field can have the following values:

• Processing statuses: processing
• Final statuses: success, failed

Note: Tracing nodes are only available for completed executions (not for processing statuses).

Step 3: Execute and Interpret the Response

After running the query, you'll receive a structured JSON response. Here's an example:

{
  "data": {
    "aiAgentLogDetails": {
      "uuid": "log-uuid-123",
      "agentUuid": "agent-uuid-123",
      "agentName": "Customer Support Agent",
      "automation": {
        "id": "1",
        "name": "Respond to Customer"
      },
      "cardId": "card-123",
      "cardTitle": "Customer Inquiry #1234",
      "status": "success",
      "createdAt": "2025-01-20T14:00:00Z",
      "finishedAt": "2025-01-20T14:00:15Z",
      "executionTime": 15.0,
      "tracingNodes": [
        {
          "nodeName": "Respond to Customer",
          "status": "SUCCESS",
          "message": "Successfully processed customer inquiry"
        }
      ]
    }
  }
}

For processing statuses, the response might look like:

{
  "data": {
    "aiAgentLogDetails": {
      "uuid": "log-uuid-456",
      "agentUuid": "agent-uuid-123",
      "agentName": "Customer Support Agent",
      "automation": {
        "id": "1",
        "name": "Respond to Customer"
      },
      "cardId": "card-456",
      "cardTitle": "Customer Inquiry #5678",
      "status": "processing",
      "createdAt": "2025-01-20T15:00:00Z",
      "finishedAt": null,
      "executionTime": null,
      "tracingNodes": []
    }
  }
}

This query provides detailed information about a specific AI agent execution, including the execution flow and any errors that occurred.