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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, and an output schema exists, so the safety and return profile are fully covered elsewhere. The description adds essentially no behavioral context of its own — nothing about language support, accuracy, size limits, or failure modes.

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?

One sentence, front-loaded with the action and ending with the result. Every clause carries information and nothing is padded.

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 two-parameter, single-purpose tool with full annotations and an output schema, the description covers what an agent needs to call it. Minor gaps remain around accepted image formats and error behavior, but they do not block correct invocation.

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%, so both parameters are documented in the schema, and the description merely echoes the base64-encoded input. It adds no meaning beyond the structured field, making the baseline 3 appropriate.

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?

States a specific verb (Run OCR), the resource (an image), the input encoding (base64-encoded bytes) and the outcome (recognized text). The image-input framing inherently separates it from parse_spreadsheet, pdf_to_markdown and url_to_clean_text, though it never names them.

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 when-to-use, when-not-to-use, or alternative routing is given. An agent must infer from the word 'image' that this is the right tool when the source is a picture rather than a PDF, URL, or spreadsheet.

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