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Moenamatics

Opus MCP Server

by Moenamatics

get_job_audit_log

Retrieve detailed audit logs of all system actions performed during a specific job execution in Opus workflow automation.

Instructions

Get detailed audit log of all system actions during job execution

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobExecutionIdYesThe job execution ID to retrieve audit log for

Implementation Reference

  • The handler function that implements the get_job_audit_log tool by making an API GET request to `/job/{jobExecutionId}/audit` and returning the response data as formatted JSON text.
    private async getJobAuditLog(args: any) {
      const { jobExecutionId } = args;
      const response = await this.axiosInstance.get(
        `/job/${jobExecutionId}/audit`
      );
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(response.data, null, 2),
          },
        ],
      };
    }
  • Input schema defining the required 'jobExecutionId' parameter for the tool.
    inputSchema: {
      type: "object",
      properties: {
        jobExecutionId: {
          type: "string",
          description: "The job execution ID to retrieve audit log for",
        },
      },
      required: ["jobExecutionId"],
    },
  • src/index.ts:226-240 (registration)
    The tool registration entry in the listTools response, including name, description, and input schema.
    {
      name: "get_job_audit_log",
      description:
        "Get detailed audit log of all system actions during job execution",
      inputSchema: {
        type: "object",
        properties: {
          jobExecutionId: {
            type: "string",
            description: "The job execution ID to retrieve audit log for",
          },
        },
        required: ["jobExecutionId"],
      },
    },
  • Switch case in the CallToolRequest handler that dispatches to the specific tool handler.
    case "get_job_audit_log":
      return await this.getJobAuditLog(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 states the tool retrieves audit logs but doesn't mention whether this is a read-only operation, if it requires specific permissions, what format the logs are in, or if there are rate limits. This leaves significant gaps for a tool that likely accesses sensitive execution data.

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

Conciseness5/5

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple retrieval tool and front-loads the key information.

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

Completeness3/5

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

For a tool with one well-documented parameter but no annotations or output schema, the description is minimally adequate. It explains what the tool does but lacks important context about behavioral traits, return format, and how it differs from sibling tools, leaving the agent with incomplete understanding.

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, clearly documenting the single required parameter. The description adds no additional parameter semantics beyond what the schema provides, but since schema coverage is high, the baseline score of 3 is appropriate.

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 verb ('Get') and resource ('detailed audit log of all system actions during job execution'), making the tool's function understandable. It doesn't explicitly differentiate from sibling tools like get_job_status or get_job_results, but the focus on audit logs provides some implicit distinction.

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 like get_job_status or get_job_results. It mentions 'during job execution' but doesn't clarify prerequisites, timing constraints, or exclusions, leaving the agent to infer usage context.

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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