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

Annotations already mark the operation as read-only and non-destructive. The description adds meaningful behavioral context beyond that: each page consumes 1 credit, starting with one page is recommended, and sort_by can surface relevant products early. This gives the agent practical expectations about cost and pagination behavior.

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-organized into purpose, use cases, and usage constraints, with no filler. Every sentence adds operational or decision-making value, and the most important scoping information is front-loaded in the first sentence.

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 8 optional parameters, no output schema, and annotated safety profile, the description covers all essentials: what is returned, when to use it, when to use an alternative, cost implications, sort strategy, and parameter exclusivity. The agent has enough context to invoke the tool correctly without further inference.

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%, so the baseline is 3. The description adds important value beyond the schema by stating that seller_id and url are mutually exclusive ('Provide EITHER seller_id OR url — never both'), by giving a concrete sort_by example, and by explaining credit cost per page. This enhances the agent's ability to construct valid requests.

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 opens with a specific verb and resource: 'Extract a seller's full product catalog,' and enumerates the returned data (ASINs, brand, category, price, Prime status, variant counts, rating data, refinement filters). This clearly identifies the tool's function and distinguishes it from sibling tools like get_seller_profile.

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 gives explicit use cases (competitor inventory analysis, stock monitoring, pricing-strategy research) and names the alternative tool with the exact condition for choosing it: 'If you need the seller's legal identity or reputation instead of their products, use get_seller_profile.' It also provides operational guidance around credits, sort_by, and the mutually exclusive seller_id/url constraint.

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