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adidas_search

Search Adidas products by keyword or category slug, with pagination, sorting, and facet filters; returns product summaries, filters, and breadcrumbs.

Instructions

Search or browse Adidas products. Searches Adidas.com product listings by keyword, or browses a category listing by taxonomy slug, with real pagination and sort options. Exactly one of query or category is required. Returns product summaries (title, price, rating, images, color variants) plus facet filter groups, sort options, and (for category browse) a breadcrumb trail. Keyword search is best-effort relevance, not a guaranteed match: an obscure keyword returns whatever Adidas's own search index surfaces. A genuinely empty keyword search returns an empty product list, and requesting a page beyond the available result pages (or an unknown category) returns a not-found error. Category values are the path segment after /us/ in an Adidas category URL (e.g. women-athletic_sneakers); they can also be read from the url fields of a search/category response's own filters and breadcrumbs. Facets are applied by composing them into the category slug rather than by a separate parameter: each filters[].values[].slug is a token you splice into the category value (e.g. category=women-black-athletic_sneakers applies the Color=Black facet, and category=women-athletic_sneakers-prime applies Shipping=PRIME). Use filters[].key (the facet's stable name, e.g. searchcolor) rather than filters[].id, which is an opaque per-deployment UUID that cannot be used to build a request. Note the token's position within the slug varies by facet, so compose from a slug you have seen rather than assuming a fixed order.

Input Schema

NameRequiredDescriptionDefault
pageNoOne-based page number, defaults to 1
sortNoSort order. Allowed values: price-low-to-high, newest-to-oldest, top-sellers, price-high-to-low. Omitted means relevance.
queryNoSearch keyword. Exactly one of query or category is required.
categoryNoCategory/taxonomy slug, the path segment after /us/ in an Adidas category URL. Exactly one of query or category is required.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so richly: best-effort (not guaranteed) keyword matching, empty keyword yielding an empty list, out-of-range pages and unknown categories returning not-found errors, and the slug-composition facet mechanism. This is exactly the behavioral context an agent needs before invoking.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and the exactly-one-of rule are front-loaded, and most sentences earn their place by conveying non-obvious mechanics. It is nonetheless a dense, long single paragraph, and the facet-composition explanation could be tightened.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, yet the description explains the return payload (product summaries with title, price, rating, images, color variants, plus facet groups, sort options, and category breadcrumbs) and documents error conditions. Complete for a 4-parameter search/browse tool.

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

Parameters5/5

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

Schema coverage is 100% (baseline 3), but the description adds substantial meaning beyond the schema: the exact form of category slugs (path segment after /us/), how filters[].values[].slug tokens splice into category, using filters[].key over the opaque filters[].id, and the warning that token position varies by facet.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource and even distinguishes the tool's two operating modes (keyword search vs. category browse) with pagination and sort. However, it never names or contrasts with sibling tools like adidas_product, adidas_store, or adidas_suggest, so the sibling differentiation that a 5 requires is absent.

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?

Gives a strong conditional rule — 'Exactly one of query or category is required' — and explains when to use search vs. browse. It also documents how to apply facets via slug composition. It stops short of naming alternative tools for adjacent needs, so no explicit alternatives/exclusions.

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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