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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds useful context by mentioning that it can search by natural language and vehicle attributes, but it does not disclose details about response size, pagination behavior, or performance implications. Given the read-only nature is covered, the description adds some value but could be more transparent about result limits.

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 extremely concise, consisting of two sentences that are front-loaded with the primary function and followed by a clear usage statement. Every word contributes to understanding the tool's purpose and ideal use case. It is efficient and easy to parse.

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 the tool's complexity (17 parameters, output schema present, and rich schema details like enums and defaults), the description is reasonably complete. The output schema likely explains the return format, so the description doesn't need to cover that. It could benefit from noting the vehicle-related parameters' purpose, but overall it covers the essential use cases. The description sets the right expectations for a search tool.

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 description coverage is only 12% (just one parameter 'pricing' has a description). The description lists the types of queries allowed but does not add specific syntax or usage examples for parameters like 'q', 'sort', or vehicle fields. Since the schema is sparse, the description partially compensates by hinting at the breadth of search criteria, but it does not provide detailed explanations for individual parameters. It is adequate for a high-parameter search tool.

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 that the tool searches for products and lists the various search criteria (natural language, SKU, MPN, GTIN, brand, price, shop, vehicle). This distinguishes it from siblings like 'get_product' (retrieves a specific product) and 'check_vehicle_compatibility' (checks compatibility). It effectively communicates the tool's role in the broader context.

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 explicitly mentions 'Use for shopping and product comparison requests,' which provides clear context for when to employ this tool. However, it does not explicitly state when NOT to use it or mention alternatives like 'get_product' for retrieving specific product details. The guidance is clear but lacks exclusionary language.

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