amazon_product: GET /

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that otherSellers triggers an extra request and 5-credit cost, that shipping parameters enable delivery-zone-aware pricing, and enumerates the returned data fields. This goes beyond a simple fetch statement and sets accurate expectations.

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?

The description is longer than minimal, but each sentence earns its place: purpose, return fields, conditional behavior, and use cases. The dense field list is justified because no output schema is present, making the enumeration valuable rather than filler.

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?

Given no output schema and no annotations, the description fully compensates by enumerating the core returned data, covering conditional behaviors like otherSellers and shipping-location pricing, and listing relevant use cases. Nothing essential for an agent to decide when and how to call this tool is missing.

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?

Schema coverage is 100%, providing a baseline of 3. The description adds meaningful semantics beyond the schema by explaining the otherSellers cost/extra-request tradeoff, how deliveryZip/shippingLocation affect pricing, and domain/language dependencies. This supplements the parameter definitions without redundancy.

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?

Description opens with a specific verb and resource: 'Fetches a single Amazon product page by ASIN on a chosen Amazon domain.' This clearly distinguishes product details from sibling tools focused on reviews, search, and seller data, even without naming them.

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?

Lists concrete use cases including product research, price/stock monitoring, listing QA, Buy Box tracking, and cross-locale analysis. This gives clear context for when to use the tool, though it does not explicitly state when not to use it or mention alternatives.

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