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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description adds useful context about output fields and the model identification input, but does not disclose additional behavioral traits such as authentication requirements, rate limits, or behavior when no results are found. Given the strong annotation coverage, a 3 is appropriate.

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 a single sentence that front-loads the verb and resource, then immediately provides the input source and expected output. Every phrase adds value with no filler or redundancy.

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 read-only, idempotent list tool with no output schema, the description provides the essential information: what to list, how to identify the model, and what the result contains. It does not mention optional year filters or the category default, but these are not required for a correct basic invocation and the core usage is fully covered.

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 0%, so the description must compensate. It does explain the core identification parameters: model_id comes from list_models, and brand+model names are an alternative. However, it does not clarify year_min/year_max or the category parameter, relying on their names and the enum to carry meaning. This is partial but not complete compensation for the lack of schema descriptions.

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 uses a specific verb and resource: 'List versions/trims for a model', which clearly differentiates this tool from siblings like list_models and list_brands. It also states what the output contains (catalog id and active listing count), so an agent can immediately understand the tool's purpose and scope.

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 gives explicit invocation guidance: either pass a model_id from list_models or use brand+model names. This provides clear context on how to call the tool and where to source the identifier. It does not explicitly state when not to use it or name alternatives, but the prerequisite relationship with list_models is sufficiently clear.

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