shop-search

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

With no annotations, the description carries the full burden. It usefully discloses that the tool itself is free, requires no API key, and that the underlying endpoints are pay-per-call via MPP. It does not describe what the tool returns or whether it performs any action beyond returning usage instructions, but for an informational tool this is a reasonable level of transparency.

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 a single sentence and front-loads the key differentiator ('FREE') before listing capabilities. The list is somewhat long but each item names a distinct feature area, so the length is justifiable for a capabilities overview.

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 zero parameters and no output schema, the description adequately conveys the tool's purpose and key constraints. However, it reads more like a feature advertisement than an actual 'how to' explanation, and it does not specify the structure or format of the usage instructions the agent will receive.

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 tool has zero parameters, which is the baseline-4 case. The description's feature list provides context for what the returned guidance will cover, and no parameter documentation is needed.

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 that this tool provides instructions for using the full paid API and enumerates the covered capabilities (product search, cart-to-checkout, ASIN snapshots, etc.). The verb is somewhat implicit ('how to use') rather than explicit, but the resource and scope are clear enough to distinguish it from a general-purpose tool.

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 word 'FREE' and the mention of 'no API key' imply this is the no-cost entry point to paid capabilities, which weakly distinguishes it from the sibling 'shop_search_preview'. However, there is no explicit statement of when to use this tool versus the preview sibling or any exclusion criteria.

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

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

With no annotations, the description carries the behavioral disclosure burden. It discloses that this is a limited preview returning only the top Amazon result, which is useful, but it does not mention latency, authentication, rate limits, or response shape. For a simple single-param lookup, this is adequate but not deeply transparent.

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 two concise sentences with the key limitation ('FREE preview', 'top Amazon result') placed upfront. It includes the alternative full version's capabilities and a usage direction without wasting words.

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 parameter and no output schema, the description is reasonably complete: it states what the tool does, its limitation, and when to use it. It could mention what the returned result looks like, but the expected response is clearly implied by 'top Amazon result'.

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 already provides 100% coverage for the single `query` parameter, including an example. The description adds essentially the same meaning ('product query'), so it does not materially enhance parameter understanding beyond the schema.

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 clearly identifies the tool as a free preview that returns the top Amazon result for a product query, and distinguishes it from the full version that returns 20+ results. The intended resource ('Shop Search' results) and operation (searching a product query) are evident, though the description does not use an explicit imperative verb like 'returns'.

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?

It explicitly says to use the tool for quick product lookups, which gives clear usage context. It also hints that the full version is appropriate when more than one result or broader coverage is needed, though it does not explicitly state exclusions or name the sibling tool as the alternative.

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