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

Annotations already indicate read-only and open-world behavior, so the description does not need to restate safety. It does add useful context by disclosing the $0.01 per-image cost. However, it does not mention output format, supported image types, size limits, or other behavioral caveats.

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 tight two-sentence definition with no filler. The core purpose is front-loaded and the pricing detail is a concise, high-value addition.

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 simple one-parameter tool, this is mostly adequate, but it lacks an explicit statement about the return value (e.g., the extracted text string) and possible edge cases such as unreadable or low-quality images. The annotations cover safety, but without an output schema, a little more behavioral detail would improve completeness.

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 schema already describes the single image parameter as 'a public https URL or a base64 data URI' with 100% coverage. The description adds no additional parameter-level meaning, so it appropriately rests at the baseline.

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 operation: 'Extract all readable text from an image.' Combined with the title 'Image to text (OCR)', this is a specific verb+resource pair that distinguishes it from sibling tools like describe_image or ai_speech_to_text.

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 explicit guidance is given about when to use this tool versus alternatives such as describe_image, analyze_image, or ai_speech_to_text. The intended use is implied by the description but not stated, and no exclusionary conditions or alternative routing are provided.

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