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Moenamatics

Opus MCP Server

by Moenamatics

execute_job

Run a workflow job by providing the execution ID and populated input values structured according to the workflow schema.

Instructions

Execute a job with populated input values. Use jobPayloadSchema from get_workflow_details to structure inputs correctly

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobExecutionIdYesThe job execution ID from initiate_job response
jobPayloadSchemaInstanceYesJob payload with all inputs populated according to workflow schema

Implementation Reference

  • The primary handler function for the 'execute_job' tool. It extracts jobExecutionId and jobPayloadSchemaInstance from args, sends a POST request to the '/job/execute' API endpoint, and returns the response data as formatted JSON text.
    private async executeJob(args: any) {
      const { jobExecutionId, jobPayloadSchemaInstance } = args;
      const response = await this.axiosInstance.post("/job/execute", {
        jobExecutionId,
        jobPayloadSchemaInstance,
      });
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(response.data, null, 2),
          },
        ],
      };
    }
  • The tool schema definition for 'execute_job', including input schema specifying jobExecutionId and jobPayloadSchemaInstance as required parameters.
    {
      name: "execute_job",
      description:
        "Execute a job with populated input values. Use jobPayloadSchema from get_workflow_details to structure inputs correctly",
      inputSchema: {
        type: "object",
        properties: {
          jobExecutionId: {
            type: "string",
            description:
              "The job execution ID from initiate_job response",
          },
          jobPayloadSchemaInstance: {
            type: "object",
            description:
              "Job payload with all inputs populated according to workflow schema",
          },
        },
        required: ["jobExecutionId", "jobPayloadSchemaInstance"],
      },
    },
  • src/index.ts:86-87 (registration)
    Registration of the 'execute_job' handler in the tool dispatcher switch statement within the CallToolRequestSchema handler.
    case "execute_job":
      return await this.executeJob(args);
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that inputs should be 'populated according to workflow schema' but fails to disclose critical traits such as whether this is a read-only or destructive operation, authentication needs, rate limits, or what happens upon execution (e.g., job status changes). This leaves significant gaps for an agent to understand the tool's behavior.

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 appropriately sized with two concise sentences that are front-loaded with the core purpose. There is no wasted text, and it efficiently conveys necessary information without being overly verbose, though it could be slightly more structured for clarity.

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 complexity of executing a job with nested parameters and no output schema or annotations, the description is incomplete. It lacks details on behavioral traits, error handling, return values, or how this tool interacts with siblings like 'initiate_job'. For a tool that likely triggers significant system actions, this leaves too many unknowns for effective agent 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, so the schema already documents both parameters thoroughly. The description adds minimal value by referencing 'jobPayloadSchema from get_workflow_details' for structuring the 'jobPayloadSchemaInstance', but this is redundant with the schema's description. No additional semantic context is provided beyond what the schema offers.

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 action ('Execute a job') and specifies the resource ('with populated input values'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'initiate_job' or 'get_job_status', which prevents a perfect score.

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

Usage Guidelines3/5

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

The description provides implied usage by referencing 'jobPayloadSchema from get_workflow_details' for structuring inputs, suggesting a dependency. However, it lacks explicit guidance on when to use this tool versus alternatives like 'initiate_job' or 'get_job_results', and doesn't mention any exclusions or prerequisites beyond the schema reference.

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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