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doubao-image-mcp

doubao-image-mcp

by haikuotianko
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doubao_models

Lists available Doubao image generation models, style option_keys, and common aspect ratios so you can select the right parameters before generating images.

Instructions

列出豆包可用的生图模型、风格 option_key 与常用比例。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "doubao_models"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
modelsYes
ratiosYes
stylesYes
defaultModelYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the whole burden. The verb 列出 implies a non-mutating lookup, and the description names the three categories returned, but it never explicitly states that the call is safe/read-only or that it takes no arguments.

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?

A single front-loaded sentence that lists exactly the three things returned; no filler, no restating of the tool name, nothing to trim.

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

Completeness4/5

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

Zero-parameter tool with an output schema and 100% schema coverage, so the return shape is already documented. The description is complete for the lookup itself; the only missing piece is what to do with the results, e.g. that option_key values are meant to be passed to doubao_image.

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 takes zero parameters, so per the baseline there is nothing for the description to disambiguate. Dropping 'with no arguments' is a minor omission, not a real gap.

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 states a specific verb (列出) and three concrete resources: 生图模型, 风格 option_key, and 常用比例. That is enough to distinguish it from the sibling doubao_image, which by name implies generation rather than a catalog lookup, though the description never explicitly names that contrast.

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?

Usage is implied rather than stated: an agent can infer you call this to discover model names and style option_keys before generating an image, but there is no explicit 'use this before X' instruction, no prerequisites, and no named alternative.

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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