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toshihikoyanase

Mong MCP Server

get_random_name

Generate random Docker-style names for applications and workflows using the MCP protocol.

Instructions

Generate a random name like Docker does.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Registration of the 'get_random_name' tool using the @mcp.tool decorator, specifying the name and description.
    @mcp.tool(
        name="get_random_name",
        description="Generate a random name like Docker does."
    )
  • The handler function for the 'get_random_name' tool. It executes the logic by calling mong.get_random_name() to return a random Docker-like name.
    def get_random_name() -> str:
        """Tool to Generate Docker-Like Random Names"""
        return mong.get_random_name()
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. It mentions the tool generates random names 'like Docker does,' which implies a specific style or format, but doesn't disclose behavioral traits such as output format, randomness characteristics, or any limitations. The description is too vague to fully inform the agent about how the tool behaves.

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: 'Generate a random name like Docker does.' It is front-loaded with the core purpose and uses the Docker analogy to add context without unnecessary elaboration. Every word earns its place, making it highly concise and well-structured.

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?

Given the tool's low complexity (0 parameters, no annotations, but has an output schema), the description is minimally adequate. It states what the tool does but lacks details on behavioral traits or usage context. The presence of an output schema means the description doesn't need to explain return values, but it should provide more guidance on when and how to use the tool effectively.

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

Parameters4/5

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

The tool has 0 parameters, and schema description coverage is 100%. With no parameters, the description doesn't need to add parameter semantics. The baseline for 0 parameters is 4, as there's nothing to compensate for, and the description adequately addresses the tool's purpose without parameter details.

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: 'Generate a random name like Docker does.' It specifies the verb ('Generate') and resource ('random name'), and the Docker analogy provides helpful context. However, since there are no sibling tools, the lack of differentiation doesn't reduce the score.

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, constraints, or typical use cases. The Docker analogy hints at a context but doesn't explicitly state when this tool is appropriate.

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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