Analyze 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 only states that AI vision models are used and supported input formats. It does not disclose behavioral traits such as output behavior, failure conditions, accuracy, or limitations (e.g., file size restrictions or model capabilities).

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 short and front-loaded with the primary purpose. The second sentence lists supported formats efficiently. It could benefit from slight restructuring to separate purpose from input types, but it remains concise and readable.

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 (4 parameters, nested options, no output schema), the description lacks completeness. It does not explain return values, analysis modes (general, palette, hierarchy, components) beyond the schema, or how to interpret results. The user would need additional context to use this tool effectively.

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 high (75%), so the baseline is 3. The description adds minimal value beyond the schema, such as reiterating supported image source formats. The prompt parameter has detailed instructions in the schema that are not echoed in the description, but the description's mention of 'supports URLs, base64, local file paths' matches the schema's imageSource description.

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 verb 'analyze' and the resource 'image using AI vision models'. It also specifies supported input types (URLs, base64, local paths). However, it does not differentiate from sibling tools like compare_images or detect_objects_in_image, leaving some ambiguity in scope.

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?

No guidance is provided on when to use this tool versus alternatives. For example, if the goal is to compare two images or detect objects, the user would need to infer that other sibling tools are more appropriate. The description offers no exclusions or context.

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