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ABLESTACK MOLD MCP Server

by ycyun

MOLD API 호출(범용)

mold_call_debug

Debug MOLD API calls by executing arbitrary commands with parameters to test and troubleshoot cloud infrastructure interactions.

Instructions

임의의 MOLD API 명령을 호출합니다. (command + params)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commandYes
paramsNo

Implementation Reference

  • The handler function for the 'mold_call_debug' tool. It flattens the input parameters using flattenParamsForMold and calls the generic callApi function with the command and flattened params, then returns the JSON stringified response.
    async ({ command, params }) => {
      const flat = flattenParamsForMold(params ?? {});
      const data = await callApi(command, flat);
      return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
    }
  • The Zod input schema for the 'mold_call_debug' tool, defining 'command' as string and optional 'params' as a record of string keys to union of primitives or nested records.
    inputSchema: {
      command: z.string(),
      params: z
        .record(
          z.string(),
          z.union([
            z.string(),
            z.number(),
            z.boolean(),
            z.record(
              z.string(),
              z.union([
                z.string(),
                z.number(),
                z.boolean(),
                z.record(z.string(), z.union([z.string(), z.number(), z.boolean()])),
              ])
            ),
          ])
        )
        .optional(),
    },
  • src/app/tools.js:9-42 (registration)
    The registration of the 'mold_call_debug' tool using server.registerTool, including title, description, inputSchema, and the handler function.
    server.registerTool(
      "mold_call_debug",
      {
        title: "MOLD API 호출(범용)",
        description: "임의의 MOLD API 명령을 호출합니다. (command + params)",
        inputSchema: {
          command: z.string(),
          params: z
            .record(
              z.string(),
              z.union([
                z.string(),
                z.number(),
                z.boolean(),
                z.record(
                  z.string(),
                  z.union([
                    z.string(),
                    z.number(),
                    z.boolean(),
                    z.record(z.string(), z.union([z.string(), z.number(), z.boolean()])),
                  ])
                ),
              ])
            )
            .optional(),
        },
      },
      async ({ command, params }) => {
        const flat = flattenParamsForMold(params ?? {});
        const data = await callApi(command, flat);
        return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
      }
    );
Behavior1/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states what the tool does (calls API commands) without any information about side effects, authentication requirements, rate limits, error handling, or what makes this a 'debug' tool versus regular tools. This is critically insufficient for a tool that can execute arbitrary commands.

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 extremely concise - just one sentence that directly states the tool's function. There's no wasted verbiage or unnecessary elaboration. However, the extreme brevity comes at the cost of completeness, making it more under-specified than optimally concise.

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

Completeness1/5

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

For a tool that can execute arbitrary API commands with complex nested parameters, no annotations, no output schema, and 0% schema description coverage, this description is completely inadequate. It doesn't explain what makes this a 'debug' tool, what commands are available, how to structure parameters, what authentication is needed, or what to expect in return. The description fails to provide the necessary context for safe and effective use.

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

Parameters2/5

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

With 0% schema description coverage for both parameters, the description must compensate but provides minimal help. It mentions 'command + params' which maps to the two parameters, but doesn't explain what valid commands are, how to structure params, or provide any examples. For a tool with complex nested parameter structures, this is inadequate compensation.

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

Purpose3/5

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

The description states the tool 'calls arbitrary MOLD API commands' which is a clear verb+resource combination. However, it doesn't distinguish this from its sibling 'mold_call' tool, leaving ambiguity about when to use this debug version versus the regular version. The purpose is understandable but lacks sibling differentiation.

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. With sibling tools like 'mold_call' available, there's no indication of when this debug version is appropriate versus the regular version, nor any context about prerequisites or constraints. The agent receives no usage direction.

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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