list_brandsList available vehicle brands with catalog IDs and active listing counts, enabling brand-specific filtering of models by brand_id for precise search results.
List available vehicle brands (makes) with their catalog id and active
listing count. Pass a brand's id as brand_id to search_vehicles/list_models
for fast, exact filtering.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Cars | |
| body_style | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds value by specifying the return contents (catalog id and active listing count) beyond what the schema or annotations provide. It does not disclose any additional behavioral traits (e.g., pagination, limits), but for a lightweight list this is sufficient.
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 sentences with no fluff. The core purpose is front-loaded, and the second sentence delivers actionable usage guidance. Every word 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 list tool, the description covers the essential information: what it lists, what it returns, and how to use the output. It lacks parameter explanations (covered under parameter semantics) and does not mention potential constraints like pagination, but these are minor for a tool that likely returns a small list. The read-only nature is already conveyed by annotations, so the description is otherwise 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 description coverage is 0%, so the description must compensate for undocumented parameters. However, the description does not explain what 'category' or 'body_style' mean or how they affect the results. The category enum is somewhat self-explanatory, but body_style is ambiguous, and the description provides no guidance, leaving a significant gap.
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 states a specific action (List) and resource (available vehicle brands/makes), and clearly distinguishes its purpose by naming the outputs (catalog id and active listing count). It also relates to sibling tools (search_vehicles, list_models), making it unambiguous what this tool is for.
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 explicitly tells the agent to pass the resulting brand_id to search_vehicles/list_models for fast filtering, which explains when and why to use this tool. It does not explicitly state when not to use it or mention alternatives like list_filter_options, but the context is clear enough for a simple list tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.