ask_about_image

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the tool answers questions but omits crucial details such as supported image formats, input constraints, error behavior, or authentication requirements. This is insufficient for an agent to anticipate side effects or limitations.

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 single, compact sentence with no fluff. It is appropriately sized for a simple tool, though it could benefit from additional context without becoming verbose. The structure is front-loaded with the core action and resource.

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 the tool's complexity (6 parameters, nested objects, multiple image input methods, no output schema, and sibling tools), the description is far too sparse. It does not explain how to choose between the various image inputs, what the output format looks like, or any usage context. The schema covers parameter details, but the description fails to provide the overarching behavioral and contextual information an agent needs.

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 baseline is 3. The description adds no additional meaning beyond the schema; it simply restates the purpose. While the schema thoroughly documents each parameter, the description does not explain the semantic distinction between the multiple image input options (URL, path, base64, structured object), which would help the agent choose appropriately.

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 multimodal model to answer specific questions about images. This differentiates it from sibling tools like 'describe_image' (general description) and 'extract_image_text' (text extraction), making the purpose distinct and actionable.

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 no guidance on when to use this tool versus the siblings. It does not mention that it is suitable for specific, nuanced questions rather than general descriptions or text extraction, leaving the agent to infer usage from the name alone.

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