Search Products

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

The description adds value beyond annotations by stating that the return is a list of ASINs and that full details require a separate call to get_product. This clarifies the tool's scope. Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description supplements with return format and next-step guidance, justifying a 4.

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 well-structured, beginning with a clear one-sentence purpose, followed by return behavior and a pointer to a sibling tool. It includes an Args section and Examples, but each element contributes meaningfully to usage understanding. No redundant filler, making it both concise and informative.

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 search tool with no output schema, the description adequately explains the return value (list of ASINs) and how to consume it. It also covers all parameters, provides examples, and notes the optional nature of category_id and domain. The description is self-contained and complete for the agent to select and invoke the tool correctly.

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%, but the description goes beyond schema by providing concrete examples that map natural language requests to parameters (e.g., "yoga mat" -> keyword). This helps the agent understand how to infer values from user intents, adding semantic value over the schema's field descriptions.

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 states it searches for Amazon products on Keepa by keyword, returns a list of matching ASINs, and distinguishes itself from get_product by explicitly directing users to use get_product for full details. This is a specific verb+resource combination that differentiates it from sibling tools.

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 provides clear context by telling users to call get_product on any returned ASIN for full details, giving a direct follow-up action. It also gives usage examples, but it does not explicitly state when not to use the tool or compare against alternatives like get_best_sellers. Thus it has clear context but no exclusions.

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