Tudetic Product Search

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

Annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context — results are 'candidates', not confirmed fits, and the user must verify on the product page. However, it omits the pricing='customer' session requirement and whether registration and make/model/year are mutually exclusive.

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 action and immediately followed by the verification caveat; no filler. It is arguably too terse for a 10-parameter tool, but nothing present 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?

An output schema exists, so return values need no explanation. Still, with 10 optional parameters at 10% schema coverage, the description leaves unresolved which parameters belong to which input mode, whether registration excludes make/model/year, and how shop/lang/limit defaults apply.

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 only 10% across 10 parameters; only 'pricing' is documented in the schema. The description names the two input styles, partially mapping to registration and vehicle_make/model/year, but says nothing about q, lang, shop, limit, or vehicle_cc, so most parameters carry no semantic explanation anywhere.

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 ('Find product candidates') and names the two input modes (registration plate vs. make/model/year), which is more specific than a generic search. It does not, however, differentiate itself from the sibling search_products/get_product tools, so an agent must infer the boundary.

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 input modes imply the scenario ('registration plate or a complete vehicle make/model/year'), but there is no explicit when-to-use, when-not-to-use, or routing to search_products/get_product. The only imperative ('Always ask the user to verify fitment') is a caution, not usage 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, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds only that details are 'current', without noting the multi-shop scope or that priced/personalized results may depend on session context.

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 front-loaded sentence with no filler, stating the resource and the two key identifiers immediately. It is efficient, though minimally so.

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?

The output schema removes any need to describe return values, and annotations cover safety, so the main gap is the undocumented shop/lang dimension and the absence of guidance on the pricing/session interaction. Adequate but leaves real ambiguity for a 5-parameter tool.

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 only 20%: lang, shop, product_id, and variant_id lack schema descriptions. The description names product_id and variant_id but adds no format, default, or constraint meaning, and never mentions the shop or lang selectors that materially change the response.

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 (retrieve) and resource (product details), and scopes it to a 'known' product ID plus optional variant, which distinguishes it from the sibling search_products. It does not name the sibling explicitly, so it lands at 4 rather than 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 word 'known' implies this is for when an ID is already in hand rather than for discovery, which is useful implicit guidance against search_products. However, no explicit when-to-use/when-not statement or reference to alternatives is given.

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, openWorldHint=true and destructiveHint=false, and the description adds no behavioral context beyond them — no pagination ceiling (page/limit), no note on result volume, and no warning that pricing=customer depends on a logged-in session (that lives only in the 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?

Two tight sentences, front-loaded with the searchable dimensions and followed by the use case; no 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?

With 17 mostly undocumented parameters, no required fields, and no output-schema explanation needed, the description is far too thin: it never clarifies which parameters interact, whether any combination is required, or how paging and sorting behave.

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 only 12% across 17 parameters, so the description carries most of the burden; it names some searchable axes (SKU, MPN, GTIN, brand, price, shop, vehicle) but omits how they combine, and says nothing about lang, page, limit, sort, category_id, registration, vehicle_cc or in_stock.

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 (find) and resource (products) and enumerates the searchable dimensions, which lets an agent distinguish it from get_product. It does not explicitly say it is the list/multi-result counterpart to get_product, but the scope is clear.

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?

"Use for shopping and product comparison requests" implies context but gives no when-not guidance and never references the siblings get_product or check_vehicle_compatibility, leaving the agent to infer when to search versus fetch or check fitment.

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