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GoldBean

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

baidu_face_detect

Detect faces in images via URL input, returning face positions and attributes. Each call costs $0.01 with limited free calls daily.

Instructions

[Face] 人脸检测 — $0.01/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_face_detect"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageYes人脸图片URL

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?

No annotations exist, so the description should disclose behavioral traits. It mentions pricing and free quota but omits details like whether the tool is read-only, what image properties are required (e.g., minimum face size), or any rate limits beyond the free tier.

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 very short, one line with no fluff. It is front-loaded with the tool's purpose. However, it omits important details that could be included without excessive length.

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?

For a tool with 1 parameter, no output schema, and no annotations, the description is insufficient. It does not explain what the tool returns (e.g., face locations, confidence scores), leaving the agent uninformed about the response structure. It also fails to differentiate usage among many similar siblings.

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 description coverage is 100% (parameter 'image' has description '人脸图片URL'). The description adds no further meaning to the parameter, so baseline score of 3 applies.

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 '人脸检测' (face detection), indicating the tool detects faces in images. This distinguishes it from siblings like baidu_face_compare which compares faces. However, it doesn't specify the output (e.g., bounding boxes, landmarks), lacking full scope.

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_object_detect or baidu_face_compare. There is no context about prerequisites or typical use cases, leaving the agent to guess.

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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