query_vehicle_info

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

No annotations provided, so description carries full burden. It discloses that the tool is a query (read-only) and lists the returned fields. Also mentions rate limit. Does not detail error handling or authorization requirements, but the behavioral traits are sufficiently communicated for a simple query tool.

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?

Description is two sentences plus a final note, each sentence purposeful. First sentence defines function and outputs, second gives use cases, third adds constraints. No wasted words, well-structured and front-loaded.

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 parameter set (2 params) and no output schema, the description covers return fields, use cases, and limits. It lacks error handling details or status codes, but is generally complete enough for an agent to use correctly.

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%, with descriptions for both parameters including examples. The description repeats the same information about plate_number and plate_color, adding no new semantics beyond what the schema already provides. Thus baseline 3 is 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?

The description clearly states the tool queries vehicle information by license plate number, listing specific fields returned (brand, model, VIN, etc.). It distinguishes from sibling tools like face_compare and ocr_recognize which are unrelated, and from vehicle_risk_score which is a different operation.

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?

Explicitly states use cases: used car evaluation, vehicle background check, fleet management. Also mentions support for standard Chinese plates and free tier limit (30 requests/day). Lacks explicit when-not-to-use or differentiation from sibling tools like vehicle_risk_score, but context is clear.

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