ocr_recognize

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It only states the basic function and does not describe output format, failure modes, image requirements, or side effects, leaving important behavior unspecified.

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 easy to read, but the phrase 'OCR recognition' is redundant and the sentence provides only a minimal summary. It is concise without being structured or informative enough to guide effective use.

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?

With five parameters, no output schema, no annotations, and related sibling tools, this description is too thin. It does not explain what the returned text looks like, how base64 input should be prepared, or how this tool relates to text_detection.

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?

The input schema has 100% description coverage, so the baseline is 3. The tool description adds no parameter-level meaning, but the schema already documents each parameter clearly, including defaults and examples.

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 states a specific action (perform OCR) on a specific resource (an image) with a clear outcome (extract text content). However, it does not distinguish this tool from the sibling text_detection, and 'OCR recognition' is slightly redundant.

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 given about when to use this tool compared to text_detection, slide_match, or slide_comparison. There are no exclusions, prerequisites, or alternative-selection hints, so the agent must 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.