describe_image

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

With no annotations provided, the description carries the full burden. It discloses behavioral traits such as automatic detection of local paths vs URLs and transparent passing of the 'detail' parameter to the API. It does not cover rate limits or auth, but the safety profile is reasonable for a read-only tool.

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 a tight two-sentence Chinese paragraph that efficiently conveys purpose, input types, and use cases without any fluff. Every sentence adds value.

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?

Given no output schema and no annotations, the description covers the main functionality and input constraints. It does not describe the return format, but the verb '描述' implies a textual description. Overall, it is fairly complete for a straightforward image description tool.

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%, so the description does not need to add much parameter info. It re-emphasizes the 'detail' and 'prompt' parameters but does not provide additional meaning beyond the schema. Baseline 3 is appropriate.

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 uses a vision model to describe image content, and lists specific use cases like UI analysis, text extraction, and object/scene recognition. It distinguishes itself from the sibling tool 'compress_image', which is for compression, making the purpose unambiguous.

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 provides clear context for when to use the tool (analyzing UI, extracting text, recognizing objects/scenes) and implicitly distinguishes from compression tools. However, it does not explicitly state when not to use or compare alternatives beyond the sibling mention.

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