list_modelsRetrieve vehicle models for a brand using its ID or name, including catalog IDs and active listing counts for market analysis.
List models for a brand (pass brand_id from list_brands, or a brand name) with each model's catalog id and active listing count.
| Name | Required | Description | Default |
|---|---|---|---|
| brand | No | ||
| brand_id | No | ||
| category | No | Cars |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds useful context about return fields and the source of brand_id, going beyond what annotations provide. No contradiction with annotations.
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, dense sentence that front-loads the purpose and includes essential input and output details. No wasted words; every phrase 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 with annotations covering safety and no output schema, the description covers the main purpose, input source, and return fields. It does not clarify behavior when neither brand nor brand_id is provided, nor explain the category filter, which are minor gaps given the 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?
Schema coverage is 0%, so the description must compensate. It explains brand and brand_id ('pass brand_id... or a brand name') but does not mention the category parameter, which has an enum with default 'Cars'. Thus, two of three parameters are explained, but category remains undocumented in the description.
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: 'List models for a brand' with specific output details ('each model's catalog id and active listing count'). It also differentiates from siblings like list_brands by referencing brand_id from list_brands, making the scope unambiguous.
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 a clear usage hint: 'pass brand_id from list_brands, or a brand name', indicating the prerequisite step of calling list_brands. It does not explicitly mention when not to use this tool or compare with list_versions, but the workflow guidance is helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.