nhtsa_complaints

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe, non-mutating operation. The description adds that all three parameters are required, which is a practical constraint. However, it does not describe potential response size, pagination, or error behavior (e.g., invalid model names), which would be valuable context. With annotations covering the safety profile, the description provides some but not extensive behavioral detail.

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?

The description is concise, front-loaded with the purpose, and includes an illustrative example. Every sentence contributes: the main purpose, the requirement for all parameters, a pointer to the sibling tool for model validation, and a clear example. This is efficient and well-structured, with no redundant information.

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?

The tool is a simple search with three parameters, all documented. The description covers the essential usage constraints (all required, use nhtsa_models) and provides an example. There is no output schema, so the description does not need to explain return values, but it could mention that the response is a list of complaints or any limits. Overall, it is adequately complete for an agent to call it correctly, with minor room for improvement on response expectations.

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?

The schema already provides descriptions for all three parameters (coverage 100%), including example values for make and model. The description adds a concrete example for model_year and clarifies that all three are required. It also gives an example of valid values ('tesla', 'model 3', 2023), which is helpful but not substantially beyond the schema's examples. Since the schema does the heavy lifting, a baseline of 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's purpose: 'Search NHTSA vehicle complaints by make, model, and model year.' It identifies a specific verb ('search'), resource ('NHTSA vehicle complaints'), and the key parameters. It distinguishes from siblings like 'nhtsa_recalls' and 'nhtsa_safety_ratings' by focusing on complaints, and it references sibling 'nhtsa_models' for validation, aiding differentiation.

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 notes that all three parameters are required by the NHTSA API, which is a clear usage constraint. It also instructs agents to use 'nhtsa_models' to find valid models for a make, providing alternative guidance. However, it does not explicitly state when not to use this tool or compare it with other complaint-related tools like 'nhtsa_complaint_detail', which could be relevant for retrieving details of a specific complaint.

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