ANKUSI Wheel Fitment

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds only that results are grouped with per-make vehicle counts; it says nothing about result size, ordering, or whether the list is exhaustive at time of call.

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?

A single sentence with no filler; the resource is front-loaded and the returned value is stated directly after it. Nothing could be removed without losing information.

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 zero-parameter enumeration tool with rich annotations and no output schema, the description covers both what is listed and what each entry carries (a vehicle count), which is most of what an agent needs. The exact field names and ordering of the returned entries are the only notable omission.

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?

The tool takes zero parameters, and the schema is an empty object, so there is no parameter meaning for the description to supply. Baseline for a parameterless tool applies.

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 resource ('All vehicle makes') and even the payload ('the number of vehicles for each'), so the agent knows exactly what it enumerates. It does not name the siblings (lookup_wheel_fitment, vehicles_by_bolt_pattern), but those are clearly different operations, so confusion risk is low.

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?

There is no explicit when-to-use statement, no mention of alternatives, and no guidance that this is the discovery step before lookup_wheel_fitment. Usage is only implied by the fact that it is a complete enumeration of makes.

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

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.

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds no behavior beyond that: it does not mention that results are capped (limit max 50 / default 20), whether matching is exact or normalized, or what happens when the pattern is unrecognized.

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 short sentences, front-loaded with the core verb and resource, with examples placed early. The second sentence is a use-case hint that slightly duplicates the first rather than adding new constraints, but nothing is padded or confusing.

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 three-parameter read tool with a fully documented schema and complete annotations, this is adequate to call correctly. It is thin on what the agent should expect back — no mention of the default 20 / max 50 result cap, ordering, or whether an empty result means an invalid pattern — which matters for interpreting 'no vehicles' answers.

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 100%, so the schema already documents bolt_pattern format with its own example and explains limit's 1-50 range. The description's extra examples (5x114.3, 6x139.7) are mildly useful for supporting 5-lug and 6-lug variants, but it never mentions the optional make filter, so it adds little beyond the schema baseline.

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?

States a specific verb and resource ('List vehicles') scoped by a named identifier ('given bolt pattern') and supplies concrete format examples (5x114.3, 6x139.7). It does not distinguish the tool from the sibling lookup_wheel_fitment, which is the closest conceptual neighbor, so it falls short of a 5.

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 clause 'Useful to check which cars a wheel will bolt onto' implies a use case (wheel-fitment research) but gives no explicit when-to-use versus lookup_wheel_fitment or list_makes, and no exclusions or prerequisites. Usage must be inferred from the phrasing rather than stated.

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