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GoldBean

GoldBean

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

baidu_car

Recognize vehicles from image URLs. Detects car makes, models, and attributes for visual vehicle identification.

Instructions

[Vision] 车辆识别 — $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": {
      "image": "<image>"
    },
    "name": "baidu_car"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageYes车辆图片URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations exist, so the description must disclose behavioral traits. It adds cost and quota information ($0.02/call, free 5/5 today), which is helpful. However, it does not explain the output format, what kind of car information is returned, or any limitations, leaving significant gaps.

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, consisting of a single line with key identifiers and cost info. It is front-loaded but lacks elaboration; however, it earns its place without fluff.

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?

With one parameter, no output schema, and no description of the return value or behavior, the tool is underspecified for an AI to fully understand its usage. The context signals (siblings, annotations) do not compensate for the lack of completeness.

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% with the parameter 'image' described as '车辆图片URL'. The tool description adds no additional semantics beyond what the schema already provides, resulting in a baseline score of 3.

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

Purpose5/5

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

The description clearly indicates this tool is for vehicle recognition under the Vision category, with a specific verb (识别) and resource (车辆). It distinguishes from sibling tools like baidu_vehicle_detect by focusing on identification rather than detection.

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 guidelines are provided on when to use this tool versus alternatives like baidu_vehicle_detect or baidu_object_detect. The description only states the function without context for selection.

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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