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zalando_search

Search Zalando products by keyword and required country storefront. Return normalized result cards with price, brand, image, and total count.

Instructions

Search Zalando products. Searches a Zalando country storefront by keyword and returns normalized result cards with price, brand, and image. Returns the first page of results as rendered by Zalando plus the upstream total_count; deeper pagination is not yet supported. market is required (there is no default storefront) and accepts 25 country storefronts — see zalando-markets for the full current list with domains.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesProduct search keyword
marketYesZalando country storefront
Behavior4/5

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

With no annotations, the description carries the full burden and discloses meaningful behavior: returns normalized result cards (price, brand, image), includes upstream total_count, limits results to the first page, and requires market with no default as one of 25 storefronts. This sets agent expectations for output and limitations beyond the basic search function.

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?

Four concise sentences, each earning its place: purpose, return format, pagination limitation, and market requirement with reference. The description is front-loaded with the core action and avoids filler, making it efficient and scannable.

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 no output schema and no annotations, the description covers essential context: what is searched, key output fields (price, brand, image), the pagination limit, total_count, and parameter requirements. It stops short of fully specifying result structure or sort order, but provides enough for an agent to invoke the tool and interpret typical results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% description coverage, so baseline is 3. The description adds crucial meaning for `market` — it is required, has no default, accepts 25 country storefronts, and the full list is available via zalando-markets — going well beyond the schema's vague 'Zalando country storefront' label.

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?

Description opens with 'Search Zalando products' and elaborates with 'Searches a Zalando country storefront by keyword', clearly specifying verb, resource, and scope. It distinguishes itself from siblings like zalando_suggest, zalando_category, and zalando_product by focusing on keyword search and returning normalized result cards, and explicitly references zalando-markets for the market list.

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?

Provides clear context for use: keyword search on a country storefront, market is required with no default, only the first page is returned (pagination not supported), and points to zalando-markets for accepted storefronts. It lacks explicit 'when not to use' statements for alternatives, but the stated constraints and sibling reference give practical guidance.

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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