carmax_vehicle_recommendations

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context: an empty list is a normal result (not an error), and the data is credential-free public data from CarMax's mobile-app API. These details set expectations for response handling and authentication, going beyond a simple purpose statement.

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 and well-structured. The first sentence states the main purpose, the second lists return values, and the third handles edge cases and data source. No redundant or irrelevant information is included; every sentence earns its place.

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 read-only tool with two required, fully described parameters and no output schema, the description is complete. It explains what the tool returns, acknowledges the empty-list edge case, and notes that no credentials are needed. An agent has sufficient information to select and invoke this tool 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 description coverage is 100%, so the input schema fully documents the two parameters. The tool description does not add further parameter-specific meaning beyond referring to 'a listing' and 'store location' in the return fields. Baseline of 3 is appropriate given the schema already handles parameter semantics.

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: 'Get CarMax similar vehicles recommendations for a listing.' It specifies the resource (a listing) and the action (get similar-vehicle recommendations), and distinguishes this tool from siblings like carmax_vehicle or carmax_search by focusing on recommendations. The listing of returned fields further clarifies what the tool does.

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 implies usage through its purpose ('for a listing') and mentions data source, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions. No sibling tools are referenced for contrast. However, the context is clear enough for an agent to infer primary use cases.

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