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AIWerk

@aiwerk/mcp-server-wheel-size

by AIWerk

list-makes

Read-only

List vehicle manufacturers (makes) for a specified market region, returning slugs used as inputs for other tools. Region-dependent availability ensures correct make identifiers.

Instructions

List all vehicle manufacturers (makes) available in a given market region. Returns slugs used as the "make" input for subsequent tools. Make availability is region-dependent, the same brand may have different slugs across markets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionYesMarket region code (e.g., "eudm" for Europe, "usdm" for North America, "jdm" for Japan). Get the full list from list-regions.
Behavior4/5

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

Annotations already indicate readOnlyHint and openWorldHint, so the bar is lower. The description adds valuable behavioral context: make availability varies by region and the same brand may have different slugs across markets. This goes beyond the annotations and helps the agent understand the variability of results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences that immediately state the function, scope, and a key behavioral nuance (region-dependency). Every sentence contributes meaning without redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple one-parameter schema, the lack of an output schema, and the presence of annotations, the description is complete. It explains what the tool does, what it returns (slugs for 'make'), and how results vary by region. This is sufficient for an agent to correctly invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the one parameter 'region', and the schema description provides examples and a pointer to list-regions. The tool description does not add additional parameter details beyond what the schema already offers, so the baseline of 3 applies as schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('List') and resource ('vehicle manufacturers/makes'). It also specifies the scope ('available in a given market region') and distinguishes itself from sibling list tools by focusing on makes. The additional detail about returning slugs makes the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: it returns slugs used as input for subsequent tools, and emphasizes that make availability is region-dependent. It does not explicitly list alternatives or exclusions, but the practical guidance about using region codes (in the schema) and the tool's role as a prerequisite for other queries is evident.

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

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