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

With readOnlyHint/openWorldHint already covering safety, the description adds substantial non-obvious behavior: it depends on local tesseract availability, degrades to UNKNOWN (has_text null) rather than 'no text', and is advisory. This fallback/null semantics is exactly the kind of operational detail annotations cannot convey.

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?

Front-loaded with the core action, then denses in the advisory and fallback behavior without padding. A stray '[#57c0af]' token at the end is noise but small.

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?

No output schema, yet the description helpfully defines the expected_text verdict path and the has_text null case. It is nearly complete for invocation, with the only gap being the untouched image_url/workspace parameters.

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 0%, so the description must compensate. It explains expected_text well (match verdict vs raw text) but says nothing about image_url, workspace, or image_uuid, leaving three of four params undocumented.

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?

Specific verb+resource: 'Read the text in a design with local OCR (tesseract)'. It is clearly distinguishable from sibling verification tools (verify_design_quality, verify_mockup_quality, check_design_compliance) because it targets text/spelling specifically.

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?

Gives explicit conditional guidance: pass expected_text for a match verdict, otherwise detected text is returned for visual review, and read the image yourself when has_text is null. It stops short of naming a sibling alternative, but the when-to-use conditions are clear.

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