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analyze_image

Provide an image URL or data URL to receive a text description from a vision model, with automatic fallback on rate limits, timeouts, or server errors.

Instructions

分析一张图片,返回视觉模型给出的文字结果。

image 可以是:HTTP/HTTPS 图片 URL、base64 data URL(data:image/...)。 按 VISION_MODELS 配置的顺序调用模型,遇限流/超时/5xx 自动切换到下一个。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
promptNo请描述这张图片的内容。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are present, so the description carries full burden. It discloses the model-fallback mechanism, accepted input formats, and that the output is text from a vision model. It does not mention authentication, rate limits, or response details, but the output schema covers return structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences effectively communicate purpose and key behavioral details. No redundant words; every sentence contributes value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has an output schema, so return values are covered externally. The description handles image format and error fallback, the core complexities. The missing prompt explanation is a notable gap but does not severely undermine overall completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain parameters. It explains the image parameter's accepted formats (URL or base64). However, the prompt parameter is not mentioned at all, and its behavior beyond a default value is undocumented. The description adds partial value but fails to fully compensate for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: analyze an image and return text results from a vision model. It specifies the resource (image) and the action (analyze), making the purpose unambiguous even without sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear context on acceptable image formats (HTTP/HTTPS URLs and base64 data URLs) and explains fallback behavior on rate limits/timeouts/5xx. However, it does not explicitly state when not to use this tool or list alternatives, though no siblings exist.

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

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