Extract text from images, including tables and handwriting. Input files using local paths or URLs to digitize visual data and convert graphical content into readable text.
识别图片中的文字内容。支持本地文件路径或 URL。
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | 图片来源：本地文件路径或 URL | |
| language | No | 识别语言，默认 'ch'（中文）。可选：ch/en/japan/korean 等 | ch |
| use_angle_cls | No | 是否启用文字方向分类，默认 true |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden, yet it says nothing about what is returned (raw text? lines? confidence?), supported image formats, size limits, or failure behavior for non-image inputs. The input-source sentence mostly restates the schema's 'source' field.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with the core capability front-loaded and zero filler. It is efficient, though the second sentence largely duplicates the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations and no output schema, the description is the only place an agent could learn what the call returns and how it behaves. It does not mention the return value (recognized text) or any operational constraints, leaving a real gap for a tool whose whole purpose is producing output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema documents source, language (with example values), and use_angle_cls with defaults, so the baseline is 3. The description adds no meaning beyond the schema, only restating that local paths and URLs are accepted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource: recognize text in an image, with supported input sources. It is clear this is the general OCR tool, but it never explicitly names the sibling variants (ocr_table, ocr_handwrite, ocr_formula) it is the default alternative to, so differentiation is only implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no when-to-use guidance and no exclusions, despite three specialized siblings existing. An agent has to infer on its own that tables, handwriting, and formulas should route to the other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.