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AIWerk

@aiwerk/mcp-server-wheel-size

by AIWerk

search-modifications-by-tire

Read-only

Find trim and modification variants for a known vehicle make and model that fit a specific tire size. Provide make, model, section width, aspect ratio, and rim diameter to get compatible options.

Instructions

Find specific trim/modification variants of a known make+model compatible with a given tyre size. Required: make, model, section_width (mm), aspect_ratio (%), rim_diameter (inches). Optional: region, limit, offset. More granular than search-by-tire. Use when you already know the vehicle.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYesManufacturer slug (e.g. "audi"). Get slugs from list-makes.
limitNoMaximum results to return (1-100).
modelYesModel slug (e.g. "a4"). Get slugs from list-models.
offsetNoNumber of results to skip for pagination.
regionNoMarket region code (e.g. "eudm", "usdm"). Get codes from list-regions.
aspect_ratioYesAspect ratio as a percentage integer 1-100 (e.g. 45 for a 45-series tyre). Use list-tire-aspect-ratios to enumerate valid values.
rim_diameterYesRim diameter in inches (e.g. 18). Must be positive. Use list-tire-rim-diameters to enumerate valid values.
section_widthYesTyre section width in mm (e.g. 245). Must be positive. Use list-tire-section-widths to enumerate valid values.
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safe-read nature is established. The description adds useful context by indicating the tool returns 'specific trim/modification variants' and that it is 'more granular' than the sibling, giving the agent a sense of output specificity without contradicting annotations.

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 concise—three sentences: purpose, required/optional params, and usage guidance. Each sentence earns its place, and the most important information (what it does) is front-loaded.

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

Completeness4/5

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

For a tool with 8 parameters and no output schema, the description covers the core purpose, required/optional inputs, and usage context. It does not describe result format or pagination details, but this is partially mitigated by schema descriptions and the simple search tool nature.

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 description coverage is 100%, so the description does not need to add param explanations. The description simply restates the required parameters with units (e.g., 'section_width (mm)') without adding semantics beyond the schema, which meets the baseline but does not exceed it.

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 states a specific verb ('Find'), a clear resource ('specific trim/modification variants'), and a precise scope ('of a known make+model compatible with a given tyre size'). It also differentiates from siblings by noting 'More granular than search-by-tire', which helps distinguish it from closely related tools.

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?

It provides explicit usage context ('Use when you already know the vehicle') and names an alternative tool ('More granular than search-by-tire'). It does not explicitly state when not to use this tool or mention other alternatives like search-modifications-by-rim, but the guidance is sufficient for basic selection.

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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