kasko_list_brands

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

Annotations already declare readOnlyHint and openWorldHint, which the description reinforces. It adds behavioral nuance by clarifying that the returned brand_id is not the brand code printed on policies, preventing misuse. It could mention the exact return format but the output schema likely covers that.

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 brief, with exactly two short paragraphs. The first sentence delivers the core purpose, and the second adds essential details. Every sentence earns its place; there is zero waste.

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 tool's simplicity (one parameter, no nested objects), the description fully covers the purpose, requirements, and the key distinction about brand_id. The output schema exists, so return values are documented elsewhere, making this description complete.

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 already describes model_year with an example, and the description emphasizes its necessity and the fact that availability varies by year. This adds meaningful context beyond the schema, such as why the parameter is required and its impact on results.

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 lists vehicle brands for a model year, using a specific verb and resource. It distinguishes from siblings like kasko_list_models by mentioning it returns brand_id for that consumer.

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 the year is required because availability differs per year, and notes the relationship to kasko_list_models. This provides clear when-to-use guidance and key context for the expected workflow.

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