bestbuy_product_related

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

With no annotations at all, the description fully assumes the burden of disclosing behavior, and it does so exceptionally. It declares the return payload (sku, name, url, image, price), clarifies the response is organic/non-sponsored, and defines the sku parameter. Most importantly, it preempts a likely error case by stating that pages without a comparison table yield an empty list rather than an exception.

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

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

Everything is front-loaded and tightly worded. The first sentence names the action and resource, the second sentence details the return format, and the third handles the edge case. No filler, no force- background, no repetition of schema fields.

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

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

For a tool with one scalar parameter and no output schema, this description is complete. It covers input semantics, output contents, output shape, and the empty-case behavior. An agent has everything needed to decide whether to call it and to understand the results.

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

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

The schema has a single parameter with 100% description coverage, so the baseline is 3. The description still adds value by explaining that 'sku' is the numeric Best Buy SKU shown on bestbuy.com product pages and URLs, giving the agent a concrete way to locate the correct value. This empirical detail goes beyond the schema's 'Numeric Best Buy SKU'.

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

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

The description states a specific action ('Get a Best Buy product's related products') and identifies the exact resource and data source ('product page's own comparison table'). It goes further by clarifying it returns only organic, non-sponsored items and lists the returned fields, making the tool's purpose unmistakable and distinguishable from sibling Best Buy tools like bestbuy_product, bestbuy_product_reviews, or bestbuy_search.

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

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

The description gives clear context about when to use this tool: when you need the organic related products from a product page's comparison table. It also implies an exception via 'A product page with no comparison table returns an empty list.' It doesn't explicitly name alternative tools, but the source is described precisely enough that an agent can reason about when to call this versus other Best Buy tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.