lookup_wheel_fitmentBolt pattern (PCD), center bore, factory wheel size and offset, plus reference flush and maximum aftermarket wheel sizes for a vehicle. Give at least a make or model; add year to narrow results.
| Name | Required | Description | Default |
|---|---|---|---|
| make | No | Vehicle make, e.g. Toyota | |
| year | No | Model year, e.g. 2019 | |
| limit | No | Maximum number of vehicle records to return (1-25) | |
| model | No | Model name or part of it, e.g. Camry |
Changes observed during successful MCP inspections.
Input schema / properties / limit / descriptionAdded value: +"Maximum number of vehicle records to return (1-25)"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this is a read-only, idempotent, closed-world operation, so the safety profile is covered. The description adds value by enumerating the returned fitment attributes, which matters because no output schema exists. It stops short of stating what happens when make/model are both omitted or whether partial model matching is fuzzy.
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?
Two sentences, no filler, and the required-input constraint is stated up front where an agent will act on it. It is slightly front-loaded on return fields rather than on the action, but nothing is wasted.
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?
Because there is no output schema, the description must carry the return-value burden and does so reasonably well by listing the fitment attributes. For a tool with all-optional parameters it is still incomplete: it does not say what is returned if neither make nor model is given, nor how truncated results (limit 1-25) are surfaced.
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 100%, so all four parameters are documented in the schema itself, setting the baseline at 3. The description adds one genuinely useful semantic constraint the schema does not enforce — that at least a make or model should be supplied, and that year narrows rather than filters outright — but says nothing about the limit parameter.
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 names the concrete data returned (bolt pattern/PCD, center bore, factory wheel size and offset, plus reference flush and max aftermarket sizes) for a vehicle, which is specific enough to distinguish a fitment lookup from a generic vehicle search. It does not name either sibling (list_makes, vehicles_by_bolt_pattern), so the differentiation from the reverse bolt-pattern lookup is left implicit.
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?
"Give at least a make or model; add year to narrow results" gives real invocation guidance for a tool with zero required parameters. However, there is no when-to-use/when-not-to-use framing and no pointer to vehicles_by_bolt_pattern for the reverse search or list_makes for enumerating makes.
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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