Search Amazon for product details, pricing, reviews, and ratings. Args: search_query: Product search query asins: List of ASINs to look up directly max_results: Max results (default 15)
| Name | Required | Description | Default |
|---|---|---|---|
| asins | No | ||
| max_results | No | ||
| search_query | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds the ability to directly look up ASINs and the default result count, but does not disclose behaviors like pagination, rate limits, or search matching semantics. It provides minimal extra context beyond annotations.
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 concise and front-loaded with the primary purpose. The Args section is efficient and to the point, with no redundant content, though it could be slightly more structured.
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?
The description is adequate for a simple read-only search tool, but it lacks clarity on return structure, pagination, and edge cases. With no output schema, the description does not fully convey what the agent can expect beyond generic categories like details, pricing, reviews, and ratings.
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 description maps each parameter to a brief explanation, such as 'List of ASINs to look up directly' and 'Max results (default 15),' adding some meaning beyond the bare schema. However, explanations are succinct and partly redundant with schema defaults, and do not delve into formats or constraints.
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 explicitly states 'Search Amazon for product details, pricing, reviews, and ratings,' using a specific verb plus resource and outcome. This clearly distinguishes the tool from sibling tools like compare_product_prices, search_fda_recalls, and search_government_contracts.
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 implies usage for Amazon product lookups but gives no explicit guidance on when to use this tool versus alternatives. No exclusions or alternative recommendations are mentioned, making the usage context unclear despite the clear purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct data source and action: product price comparison, business registration lookup, Amazon product search, FDA recalls, and government contracts. There is no meaningful overlap; even the two product-related tools are clearly separated by scope (cross-platform vs. Amazon-specific).
All tool names follow a consistent verb_noun pattern in snake_case (compare_product_prices, lookup_business_registration, search_amazon_products, etc.). Though the verbs vary, the structure is uniform and predictable.
With exactly 5 tools, the surface is well-scoped for a data lookup server. Each tool covers a distinct domain without redundancy or bloat, making the set feel curated and manageable.
The server provides comprehensive read-only search coverage across its stated data domains: product pricing, business registry, Amazon catalog, FDA safety, and federal spending. There are no obvious gaps for a lookup-oriented tool set.