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digeguigui

digeguigui

by Gaoshan0971
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

identify_turtle

Upload a turtle image in base64 format to identify its species using AI. If confidence is 70% or higher, the tool provides a direct conclusion.

Instructions

拍照识龟 — 上传龟类图片base64，AI识别品种+置信度。置信度≥70%直接给结论

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_base64": "<image_base64>"
    },
    "name": "identify_turtle"
  }
}

Input Schema

NameRequiredDescriptionDefault
image_base64Yes图片base64编码字符串

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It reveals that the tool uses AI, returns species and confidence, and has a direct conclusion threshold at 70% confidence. This adds useful context beyond the schema. However, it does not mention error handling, auth requirements, or limitations (e.g., need for clear turtle image).

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 extremely concise—two sentences in Chinese. It front-loads the purpose and immediately states the key behavioral rule (confidence threshold). Every word serves a purpose, with no fluff or redundant information. This is an ideal length for quick comprehension.

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?

Given the lack of output schema and annotations, the description does a good job covering the core functionality: it specifies the input format (turtle image base64), the output (species + confidence), and a key behavioral rule (direct conclusion at ≥70%). Missing elements include error handling (e.g., poor image, no turtle detected) and any rate limits, but these are acceptable gaps for a simple tool. The description is fairly complete for its complexity.

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 schema describes the parameter 'image_base64' as a base64 string. The description adds the semantic context that the image should be of a turtle ('龟类图片'), which is critical for correct invocation. With 100% schema coverage, the baseline is 3, and the description provides additional meaning beyond the schema, justifying a 4.

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 states the tool's purpose: identifying turtle species from an image using AI, with confidence scoring. The verb '拍照识龟' (take photo to identify turtle) and the mention of 'AI识别品种+置信度' specifically convey the action and output. It is distinct from sibling tools like get_species_profile or search_species, which handle different operations.

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?

The description does not provide explicit guidance on when to use this tool versus alternatives, such as 'use get_species_profile for known species details'. The intended use case (image-based identification) is implied, but no when-not-to-use or alternative references are given. The threshold behavior (confidence ≥70%) offers some usage context, but lacks comprehensive guidelines.

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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