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adidas_product

Fetch normalized details for one Adidas SKU: name, brand, category, description, pricing, images, and size variants. Provide a product_id from search results or a product page URL.

Instructions

Get an Adidas product. Returns normalized product-detail data for one Adidas SKU: name, brand, category, description, pricing (current/standard/sale), images, and every purchasable size variant. product_id is the Adidas SKU (e.g. JI0397), taken from a search result's products[].id field or the trailing segment of an Adidas product page URL. An unknown product_id returns a not-found error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYesAdidas SKU/product id, from a search result's products[].id field

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.0

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are present, so the description carries the full disclosure burden. It states the tool is a read operation returning normalized product-detail data, lists the returned fields, and discloses the not-found error condition. While it does not cover rate limits or other potential failure modes, for a simple single-SKU lookup this is adequate transparency.

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?

Three sentences cover purpose, output content, parameter derivation, and error behavior with zero redundancy. The core action is front-loaded, making the description easy to parse quickly.

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?

For a one-parameter tool with no output schema and no annotations, the description is complete: it explains what the tool returns, where the input comes from, and what happens on failure. Nothing essential for invoking it correctly or interpreting its results is missing.

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?

The schema already documents product_id fully (100% coverage), but the description goes far beyond it: it gives a concrete SKU example (JI0397), explains two distinct ways to derive the value (search result field or URL segment), and states the error behavior for invalid IDs. This materially improves an agent's ability to supply the correct value.

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 uses a specific verb ('Get') and resource ('Adidas product'), and immediately clarifies it returns detail for a single SKU. The enumerated return fields (name, brand, category, pricing, images, size variants) make it distinct from search/list siblings without needing to open the schema.

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?

The description clearly states the prerequisite: you need an Adidas SKU, and it tells the agent exactly where to obtain it (from a search result's products[].id field or a product page URL). It also discloses the not-found error behavior for unknown IDs. It does not explicitly name alternative tools, but the context is unambiguous enough for an agent to decide when to use this tool.

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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