Get Models For Make

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

No annotations are present, so the description must carry the behavioral burden. The verb 'List' transparently signals a read-only operation, and the description states the optional narrowing behavior with a concrete example. It does not go into error cases or edge behavior, but for a simple look-up tool the core behavior is adequately disclosed.

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 two short sentences, front-loading the main purpose and then clarifying the optional filter with an example. Every sentence contributes; there is no redundancy or fluff.

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 the simple 2-parameter shape, complete schema descriptions, and presence of an output schema, the description covers what an agent needs for a correct call. The only minor gap is the absence of explicit routing guidance among siblings, but that is not essential for this tool's 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?

The input schema already documents both parameters at 100% coverage, so the baseline is 3. The description adds value by explaining that vehicle_type narrows the result set and by giving the car-versus-motorcycle example, reinforcing the parameter's intended effect. It doesn't add new details about the make parameter beyond the schema.

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 opens with a clear directive: 'List all models for a given make.' This names the exact verb, resource, and scope, and the optional vehicle_type filter explains the only variant. It is easy to distinguish from siblings such as get_all_makes or get_model_years because the tool's target resource is explicitly 'models'.

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 establishes the obvious use case—retrieving models for a specified make—and the optional filtering context. However, it never explicitly says when to prefer this over sibling lookup tools or when not to use it, leaving tool selection to inference from the names.

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