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get_task_logs

Retrieve execution logs for a specific task to monitor performance and troubleshoot issues in workflow management.

Instructions

Get execution logs for a specific task. Returns log entries generated during task execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskIdYesThe unique task execution ID

Implementation Reference

  • The handler implementation for the 'get_task_logs' tool. It extracts the taskId from arguments, makes a GET request to the Conductor API endpoint `/tasks/${taskId}/log`, and returns the response data as a formatted JSON string in the MCP response format.
    case "get_task_logs": {
      const { taskId } = args as any;
      const response = await conductorClient.get(`/tasks/${taskId}/log`);
      
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(response.data, null, 2),
          },
        ],
      };
    }
  • Input schema definition for the 'get_task_logs' tool, specifying that a 'taskId' string is required.
    inputSchema: {
      type: "object",
      properties: {
        taskId: {
          type: "string",
          description: "The unique task execution ID",
        },
      },
      required: ["taskId"],
    },
  • src/index.ts:467-481 (registration)
    Registration of the 'get_task_logs' tool in the tools array, including name, description, and input schema. This array is returned by the list_tools handler.
    {
      name: "get_task_logs",
      description:
        "Get execution logs for a specific task. Returns log entries generated during task execution.",
      inputSchema: {
        type: "object",
        properties: {
          taskId: {
            type: "string",
            description: "The unique task execution ID",
          },
        },
        required: ["taskId"],
      },
    },
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns log entries but doesn't specify format, pagination, rate limits, authentication requirements, or error handling. For a read operation with zero annotation coverage, this leaves critical behavioral traits undocumented, though it doesn't contradict any annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, consisting of two clear sentences that directly state the tool's function and output. There's no unnecessary information or redundancy, making it efficient to parse, though it could be slightly more structured by explicitly separating purpose from behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain the return format of log entries, potential limitations, or how it fits into the broader context of task management with many sibling tools. For a tool with no structured behavioral data, more detail is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with 'taskId' clearly documented as 'The unique task execution ID'. The description adds no additional parameter semantics beyond this, such as examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema handles the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('execution logs for a specific task'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get_task_details' or 'get_task_definition', which might also retrieve task-related information, leaving some ambiguity about its unique role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, such as needing a valid task ID from another operation, or clarify its scope relative to siblings like 'get_task_details' (which might include logs or other metadata). This lack of context could lead to confusion in tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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