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GoldBean

by wuzenghai616-lang
OverviewSchemaSourceRelated ServersDiscussions(4)Admin
JavaScript
Remote

baidu_vision_chat

Analyze images and answer questions using ERNIE-VL multimodal vision understanding. Send an image URL and a question to get AI-generated responses.

Instructions

[LLM] 视觉理解对话（ERNIE-VL 多模态） — $0.02/call (free: 5/5 today)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "message": "<message>",
      "image": "<image>"
    },
    "name": "baidu_vision_chat"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageYes图片URL
messageYes提问内容

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but only discloses cost and free quota. It does not state whether the tool mutates data, requires authentication, or has side effects. Behavioral traits like response format or data handling are absent.

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 a single line that conveys essential information: tool function, model name, and pricing. It is concise and avoids redundancy, though it could be more structured.

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 no output schema, the description should hint at return values but does not. It lacks information on what the agent can expect as output, such as answer text or confidence scores. For a multimodal chat tool, this is a notable gap.

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?

Schema coverage is 100%, so the schema already documents the two parameters. The description adds minimal meaning beyond '图片URL' and '提问内容' by hinting at a chat interaction. It does not clarify expected input formats or constraints.

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 indicates this is a visual understanding dialogue tool using ERNIE-VL multimodal model, which distinguishes it from siblings like baidu_llm_chat (text-only) and baidu_image_recognition (classification). However, it lacks an explicit verb like 'answer' or 'process' and does not state the action clearly.

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?

No guidance on when to use this tool versus alternatives such as baidu_object_detect or baidu_deepseek_ocr. The description only provides pricing and does not mention context or exclusion criteria.

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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