Rack Warehouse fitment

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description usefully discloses the response semantics ('yes' with fit options/price/page, 'not listed', 'by what it mounts to') and that it reports required parts and checkout prompts — genuine behavioral context given there is no output schema.

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?

Three sentences, each carrying information, but the first sentence is a dense run-on that nests quoted answer strings and is hard to parse on first read. Purpose is front-loaded, but structure could be cleaner.

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?

With no output schema, the description does the necessary work of describing return values and required-parts reporting, and it documents the product parameter. It is largely complete, though it leaves the check_fit vs what_fits boundary ambiguous.

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 80%, and the one undocumented parameter (product) is explicitly explained in the description as a page URL, handle, or SKU, compensating for the gap. It adds real meaning beyond the structured fields rather than restating them.

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 — whether one product fits one vehicle — and enumerates the possible answers, so an agent knows the operation. It does not differentiate itself from the sibling what_fits, which sounds like an overlapping fit-check, 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?

There is no explicit when-to-use guidance and no mention of the alternatives (find_vehicle, what_fits) that an agent must choose between. Usage is only implied by the description of the answer values.

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=true and openWorldHint=false, so the safety profile is covered. The description usefully adds that results are constrained to vehicles with Rack Warehouse fitment and include roof types, but says nothing about fuzzy-match behavior, ambiguous inputs, or what happens when no vehicle matches.

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, front-loaded with the core transformation and followed by the chaining instruction. No filler, no restating of the title.

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 one-parameter read-only resolver with no output schema, the description covers the input shape and what comes back (make, model, roof types). Only the failure/ambiguity path is unaddressed, which is a minor gap 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?

The single query parameter has 0% schema description coverage, so the description must carry the load. It does add real value by giving literal input examples ('2019 tacoma', 'subaru outback'), clarifying that free-form strings are acceptable, but it omits expected format boundaries and no-match handling.

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 a specific transformation (shopper's free-text words → vehicles Rack Warehouse has fitment for) and adds what is returned (make, model, roof types). It also gestures at differentiation by telling the agent to feed the returned make/model to 'the other tools', positioning it as a resolver rather than a fitment checker like what_fits, though it never names that sibling explicitly.

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?

Usage is implied by the input framing ('the shopper's words') and the chaining note 'Use the make and model it returns with the other tools.' There is no explicit statement of when to use this versus check_fit, what_fits, or search_products, and no exclusion guidance.

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=true and openWorldHint=false, so safety is covered. The description adds substantive context beyond that by disclosing the shape of the returned payload (which fields are included) and the scope boundary around vehicles — valuable given there is no output schema.

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?

Effectively two sentences, with the routing caveat placed at the end where it reads as a guardrail. The comma-delimited field inventory is dense, but since no output schema exists each item carries information rather than padding.

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 one-parameter read tool with no output schema, the description supplies the missing return-content picture and the sibling boundary. What it omits — behavior on an unresolvable handle/SKU, or identifier precedence when several forms could match — is minor but non-trivial.

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% and the single parameter already documents 'rackwarehouse.com page URL, handle or SKU'. The description adds no format, resolution or ambiguity guidance beyond the schema, so the baseline 3 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?

Names a specific resource (one product) and enumerates exactly what comes back — price/sale, availability, variants, specs, mounts, required products, rating/reviews. It also explicitly separates itself from the vehicle-lookup siblings, so an agent can route without opening the schema.

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?

Provides an explicit when-not ('It does not list vehicles: use check_fit for one') with the named alternative, which is the main routing ambiguity for this tool. It lacks positive framing of when to reach for it (e.g., when you already hold a handle/SKU/URL), so it falls short of full when/when-not coverage.

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 establish readOnlyHint and that this stays within a closed catalog, but the description adds real behavioral value beyond them: a hard cap of eight results, and the shape of each entry (price, review count, fit by vehicle or mount, page). It does not say what happens on zero matches, but the substantive constraints are disclosed.

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?

One dense sentence that front-loads the core action and appends filters and return fields; nothing is redundant. It borders on list-heavy, but every clause carries 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?

With no output schema, the description usefully enumerates returned fields and the result cap, and annotations cover the safety profile. The main omission is failure/empty-result behavior, but for a bounded four-parameter search tool this is largely complete.

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 all four parameters are already documented with examples in the schema. The description restates them (query as 'shopper's words', brand, category, price ceiling) without adding syntax, defaults, or clarification beyond what the schema provides, so the baseline of 3 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?

States a specific verb (Search) and resource (Rack Warehouse's catalog) and characterizes the operation precisely: free-text search like the site's search box, returning up to eight products with defined fields. This is clearly distinguishable from get_product (id lookup) and check_fit/what_fits (fit queries), though it never names those siblings explicitly.

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 'search box' framing implies the usage context (natural-language shopper query, optionally narrowed by category/brand/price), which is good implicit guidance. However, it offers no when-not guidance and never points to check_fit, what_fits, or get_product as alternatives for fit or single-product lookups, so the agent must infer routing.

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=true and openWorldHint=false, so the safety profile is covered. With no output schema, the description earns credit for disclosing return behavior: the two response shapes, the eight-product cap, and the special case where carriers return their mounting points and base racks. It omits pagination/rate-limit details, keeping it out of the top band.

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 core fact (what fits one vehicle) is front-loaded in four words, and the two mode branches follow in order. The second sentence is dense and comma-heavy but every clause carries distinct payload information rather than filler.

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 five-parameter, no-output-schema read tool, the description covers both request modes and the shape of what comes back, which is what an agent needs to call it correctly. It leaves the relationship to check_fit and the source of vehicle handles (beyond the schema's find_vehicle hint) unstated, a minor but real gap.

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 explains make/model/year/category/roof_type with examples. The description reinforces how category changes behavior but adds no syntax or format detail for year, model, or roof_type beyond what the schema provides, which is the expected 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?

The description names a specific verb+resource (what fits one vehicle) and enumerates the return payload for both modes, so the agent knows exactly what this tool produces. It does not, however, distinguish itself from the closely related check_fit sibling, so the purpose is clear but not fully routable without opening the other tool's schema.

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?

It implicitly tells the agent when to include a category: omitting it yields per-category counts and handles, supplying it yields up to eight concrete products with fits and prices. That is useful branch guidance, but there is no explicit when-to-use-this-vs-check_fit-or-search_products statement and no stated prerequisites beyond the schema's hint that find_vehicle supplies handles.

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