ocr_image

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

With no annotations, the description bears full burden. It explains the local OCR engine and supported input types but does not disclose limitations (e.g., language support, accuracy, behavior on unreadable images). This is adequate but not comprehensive.

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 well-structured: a clear one-liner, technical details, and sample prompts. Every sentence adds value. It is concise without omitting necessary information.

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 single-parameter tool with an output schema, the description covers the input, technology, and usage examples. It misses potential details like language support or error handling, but overall it is sufficiently complete for effective usage.

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 has 0% description coverage, so the description must compensate. It does so excellently: 'image_source: Local file path or base64-encoded image data.' This adds critical meaning beyond the schema's bare type string.

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 'Extract text from an image using local OCR.' It specifies the verb (extract), resource (text from image), and distinguishes from siblings by emphasizing local execution and no internet needed. Examples of use cases further solidify its purpose.

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 context like 'No internet connection needed' and sample prompts, which imply when to use. However, it lacks explicit when-not-to-use advice or comparisons to sibling tools like 'read_document', which could be alternatives.

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