ocr_image

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

No annotations are provided, so the description carries the full burden. It does not disclose read-only nature, error handling (e.g., no text found), or return format. The model restriction is mentioned but other behavioral traits like resource consumption or side effects are omitted.

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?

The description is brief (two sentences) and front-loaded with the purpose. The Chinese note is important but adds some clutter; an English-only agent might need parsing. Still, the structure is efficient with no wasted words.

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?

No output schema is provided, and the description does not explain what the tool returns (e.g., extracted text, structure). With 7 parameters, details like maxTokens behavior, detail levels, and model override are not mentioned, leaving significant gaps for an agent to use the tool correctly.

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 coverage is 71% (5 of 7 parameters have descriptions). The description adds context for 'language' and 'preserveLayout' as optional hints, but most parameter semantics are already in the schema. The _caller_model parameter's schema description already includes the restriction; description does not add beyond that.

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?

The description clearly states the tool extracts visible text from an image, which matches the name 'ocr_image'. It mentions optional language and layout hints, distinguishing it from sibling tools that answer questions, compare, or describe images. However, it does not explicitly differentiate from siblings.

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 includes a model restriction note ('仅限 GLM/DeepSeek 系列模型调用'), which is a usage guideline. But it lacks explicit when-to-use or when-not-to-use guidance compared to sibling tools (e.g., use for text extraction, not for image interpretation).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.