Recognize handwritten text from images using local file paths or URLs. Specify language for accurate extraction of handwritten content.
识别图片中的手写文字内容。
| 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） | ch |
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 accuracy expectations for messy handwriting, supported image formats, or what is returned. For a read-only OCR call the risk is low, but the behavior is essentially undocumented.
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?
A single front-loaded sentence with zero waste. It is efficient, though its brevity borders on under-specification rather than pure conciseness.
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?
Parameters are fully covered by the schema and there is no output schema to explain, but with no annotations and no mention of return format or limitations, the description leaves meaningful gaps for an OCR tool with four siblings to distinguish among.
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%, with both 'source' (local path or URL) and 'language' (default 'ch') fully documented in the schema. The description adds nothing beyond the schema, so the baseline of 3 applies.
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: recognizing handwritten text in images. The word '手写' (handwritten) implicitly distinguishes it from the general-purpose sibling ocr_recognize, but it does not name that sibling or explicitly clarify the boundary against ocr_table/ocr_formula.
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?
Usage is only implied — an agent can infer this is the tool for handwritten (as opposed to printed) content, but the description gives no explicit when-to-use/when-not or any mention of the sibling alternatives ocr_recognize/ocr_table/ocr_formula.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.