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bestbuy_product

Retrieve a Best Buy product's normalized details using a numeric SKU, including price, availability, rating, and images, sourced from the product page's structured data.

Instructions

Get a Best Buy product's detail. Returns one Best Buy product's normalized detail (name, brand, model, color, price, availability, rating, images, breadcrumbs), sourced from the product page's own schema.org Product structured-data block. sku is the numeric Best Buy SKU shown on bestbuy.com product pages and URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skuYesNumeric Best Buy SKU
Behavior4/5

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

With no annotations provided, this description carries the behavioral burden itself. It states that the tool returns normalized product data sourced specifically from the product page's schema.org Product structured-data block, which is a meaningful and non-obvious behavioral disclosure. It doesn't cover failure or missing-data cases, but for a simple read-style lookup this is substantially transparent.

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?

Two tight sentences with no waste. The action and returned content are front-loaded, the source explanation earns its place, and the SKU clarification is placed last where contextual detail belongs.

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?

There is no output schema, so the description correctly compensates by enumerating the normalized return fields. With exactly one required parameter, a named product source, and clear output expectations, the description is complete enough for an agent to select and call the tool with minimal risk of confusion.

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?

The schema already fully documents the single parameter with the text 'Numeric Best Buy SKU', so the baseline is strong. The description adds value by explaining where to find the SKU on bestbuy.com product pages and URLs, which helps an agent correctly source and format the identifier.

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?

Uses a specific verb and object ('Get a Best Buy product's detail') and explicitly lists the returned normalized fields such as name, brand, color, price, availability, rating, images, and breadcrumbs. This makes it easy to distinguish from siblings like bestbuy_product_reviews, bestbuy_product_questions, and bestbuy_product_related.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The intended use is implied: provide a known Best Buy SKU to fetch one product's detail, with the SKU located on bestbuy.com pages/URLs. However, it never explicitly says when not to use it or points the agent to alternatives such as bestbuy_search for finding SKUs or bestbuy_product_reviews for ratings content.

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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