截图 OCR

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

No annotations exist, so the description carries full burden. It discloses character-level extraction and preservation of reading order/layout, but lacks details on limitations (e.g., handwriting, font types) or how it handles different image qualities. Adequate but not deeply transparent.

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?

Two sentences, front-loaded with key action. Efficient and to the point. Slight improvement could be adding structured examples or explicit scope, but no extraneous content.

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?

Given 6 parameters and an output schema, the description gives minimal high-level context. It doesn't discuss region, question, thinking, lang_hint, or detail_level behavior. Schema fills gaps but description could be more complete for agent understanding.

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 coverage is 100%, so baseline is 3. The description does not add parameter details beyond what the schema provides, but the schema itself is descriptive. The description's value lies in overall context, not per-parameter enhancement.

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 that the tool extracts text from screenshots character by word, preserving reading order and layout. It specifies supported content types (code, terminal, errors, documents), making the purpose specific and distinct from general image analysis siblings.

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 a clear when-to-use instruction: 'Use when you need to read text from the image.' It implies not to use for non-text image analysis, though it does not explicitly exclude alternatives or name sibling comparisons.

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