describe_image

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

With no annotations, the description carries full responsibility. It mentions '基于视觉模型' (vision model based) but does not elaborate on output format, limitations, or side effects. It also references '输入约定同 analyze_image' without specifying those conventions, leaving behavior opaque. Some context is given but insufficient for a fully transparent description.

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 very concise: two sentences, no fluff, directly states purpose and when to call. It is well-structured with a clear trigger and a reference for input conventions. However, the conciseness comes at the cost of completeness, but for the dimension of conciseness and structure, it is efficient.

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?

The description fails to provide comprehensive guidance: no exclusions, no detail on output, no mention of what happens for invalid input, and no standalone parameter explanation. The context signals show no annotations and 0% parameter coverage, so the description must compensate but only partially does by reusing analyze_image's conventions. For a simple tool this may be acceptable, but for an AI agent making decisions, it's insufficient.

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 0%, meaning no parameter descriptions are provided in the schema. The description mentions '输入约定同 analyze_image' which implies conventions are shared, but since analyze_image's conventions are not spelled out here, the agent must look elsewhere. The description lists only 'detail' and 'images' names without explanation. This adds minimal clarity, and the description does not compensate for the missing parameter docs.

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's action ('详细描述图片内容' = describe image content in detail) and specifically mentions the vision model basis. While it doesn't explicitly contrast with sibling tools, the phrasing '当用户要求...' distinguishes it from extract_text_from_image which focuses on text extraction. Purpose is clear and specific.

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 explicit trigger conditions ('当用户要求描述/介绍一下这张图、看到什么时调用') and points to analyze_image for input conventionsastra. However, it does not mention exclusions or when to prefer extract_text_from_image over this tool, so some guidance is missing.

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