vehicle_license_ocr

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

No annotations provided, so description carries full burden. It discloses what each page returns (main page fields, supplementary page fields), adding transparency beyond the schema. No contradictions.

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 concise sentences. Front-loaded with core purpose, immediately followed by output details and use cases. No unnecessary words.

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 two-param OCR tool without output schema, the description adequately covers inputs (via schema) and outputs (per page). Missing aspects like error handling or image requirements, but overall sufficient given tool simplicity.

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%, baseline 3. Description adds value by explaining the effect of the 'side' parameter (main vs. supplementary page outputs), which is not fully captured in the schema's brief enum description.

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 it extracts structured fields from a Chinese vehicle license, specifies fields per page, and lists use cases. It distinguishes from sibling OCR tools (id_card_ocr, driver_license_ocr) by targeting vehicle licenses.

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?

Provides explicit use cases (auto loans, fleet onboarding, etc.), giving context for when to use. However, no direct comparison with sibling tools or exclusions for alternative tools.

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