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

Annotations already establish that this is read-only, idempotent, and non-destructive. The description adds useful context beyond those annotations by enumerating the expected output fields (title, price, rating, etc.) and by demonstrating the _apiKey auth requirement in the example. It does not expose rate-limit or cost behavior, but the annotation coverage lowers the bar for this dimension.

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 focused sentence followed by one practical example. It front-loads the action and resource, then lists useful output fields, with no repetition or 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?

For a single-product lookup with a simple parameter set, the description is nearly complete: it states the purpose, names the response fields, and provides a fully parameterized example, which compensates for the lack of an output schema. It falls just short of full completeness because it does not explicitly differentiate this tool from the sibling scraping/search tools.

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 input schema already documents all four parameters with 100% coverage, so the description does not need to re-explain them. The inline example shows a realistic invocation, but it largely duplicates the schema-provided examples rather than adding semantic value beyond them.

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 uses a specific verb ('Get') with a specific resource ('structured Amazon product data') and the unique lookup key 'by ASIN.' It lists the returned fields, and by emphasizing ASIN-based structured data it is clearly distinct from siblings like scraperapi_amazon_search and scraperapi_scrape.

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 'by ASIN' qualifier implies the intended use case: fetch product data when you already have a product identifier. The example shows a concrete invocation, but the description never explicitly states when to prefer this tool over alternatives such as scraperapi_amazon_search or scraperapi_scrape, nor does it mention when not to use it.

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