describe_image_structured

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

No annotations were provided, so the description must carry the behavioral disclosure burden. It does so by stating that recognition failure returns '{"error": "..."}' instead of None, which clarifies the failure contract. It also reads as a read-only extraction operation ('extract') and documents the output shape, giving the agent useful information beyond the input schema.

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 efficiently organized: a one-sentence purpose, an Args section for the parameter, and a Returns section with error handling. It avoids fluff, repeats no schema information, and each line earns its place.

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?

For a one-parameter tool with no annotations and no output schema, the description covers the required input, the expected return keys, and the failure mode, which is enough for basic invocation. It would be more complete if it gave interaction between 'type', 'note', and 'text' or guidance on which images are out of scope, but nothing critical is missing.

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?

The input schema provides only a bare string property named 'image_path', while the description adds that it must be a local image file path ('本地图片文件路径'). That is genuine semantic added value over 'string' and enough to resolve the one required parameter, although it does not discuss supported formats, relative vs absolute paths, or preprocessing behavior.

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 identifies the action ('extract') and resource ('images with numeric annotations including vectors, matrices, coordinates, angles, unknowns'), which makes the tool's purpose specific and distinct from plain image captioning. It also enumerates the expected return keys, reinforcing the structured-recognition scope. It stops short of a 5 because it never explicitly contrasts itself with the sibling tools 'describe_image' and 'describe_image_stats'.

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?

'结构化识别' and the list of extracted quantities imply the intended use: when an agent needs numerical/structured details from an image rather than general description or statistics. However, the description does not explicitly say when to choose this tool over the named siblings or when not to use it, so the guidance is mostly implied rather than stated.

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