ocr_image

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

No annotations are provided, so the description carries the burden. It does disclose that multi-image calls 'return a section per image label', which is a useful behavioral trait. However, it omits potential limitations (e.g., language support, handwritten text, supported formats) or side effects, leaving a moderate transparency level.

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 extremely concise: two sentences. The first sentence states the primary purpose, and the second adds the key multi-image behavior. Every word earns its place with no filler or redundancy.

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?

For a 4-parameter tool with a rich schema and no output schema, the description covers the core purpose and important multi-image output behavior. It could have added explicit differentiation from the similar-sounding 'extract_from_images' sibling, but the overall context is sufficient for selecting this 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%, and every parameter already has detailed meanings in the schema. The description's mention of 'a section per image label' adds context to the images array's label property, but that is minor. It doesn't further explain parameters beyond the schema, so the baseline of 3 holds.

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 opens with 'Extract readable text from one or more images' – a specific verb and resource that clearly defines OCR functionality. Examples (screenshots, documents, diagrams, error dialogs) further clarify the intended use. The multi-image note distinguishes it from single-image analysis tools like describe_image or analyze_image.

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 clearly implies when to use: whenever readable text needs to be extracted from images, with multiple image example types. The multi-image behavior is stated, but there is no explicit exclusions or naming of alternative tools (e.g., extract_from_images) for when not to use this tool.

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