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JavaScript
Remote

adidas_suggest

Fetch Adidas search-as-you-type suggestions for a partial query and return matching products with title, URL, image, and price.

Instructions

Get Adidas search suggestions. Returns the top matching products for a partial query, the same search-as-you-type preview Adidas's own search box shows. Adidas has no separate term-autocomplete index, so each suggestion is a matching product (id, title, url, image, price) rather than a completed search phrase. Best-effort relevance: an obscure query returns whatever Adidas's own search surfaces.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesPartial search query

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden. It discloses that Adidas has no separate term-autocomplete index, that suggestions are matching products rather than phrases, and that relevance is best-effort without guarantees for obscure queries. It does not detail pagination or exact result count, but the key behavioral quirks are documented impressively.

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 sentences, each informative: what it does, product-based results, absence of autocomplete index, and best-effort caveat. Front-loaded and no filler.

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?

Given a single parameter, no output schema, and no annotations, the description covers return shape, operational behavior, and expectations. Could mention count limits or formatting variations, but it is complete for practical invocation.

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

Parameters3/5

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

Schema coverage is 100% and the only parameter, query, is described as 'Partial search query'. The description adds the meaning that the query feeds the search-as-you-type preview, but it doesn't provide examples or length/format constraints beyond the schema. Baseline 3 is appropriate.

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?

The description clearly states it returns Adidas search suggestions for a partial query, as a search-as-you-type preview, and distinguishes the actual return type (matching products with id, title, url, image, price) versus completed search phrases. The specific verb 'Get' plus resource and behavior makes it clear among many suggest siblings.

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?

It explains when to use the tool (for partial queries / as-you-type preview) and distinguishes it from a hypothetical completed-phrase autocomplete. It could explicitly mention an alternative like adidas_search, but the description conveys the context well.

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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