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

Annotations already cover the safety profile (readOnlyHint, destructiveHint=false), but the description adds substantial non-obvious behavior: it is a pure data fetch with no AI analysis, it returns nothing and answers 'MARKETPLACE NEEDED' without a marketplace, money is in local currency, and it imposes a mandatory output contract for 'Account notice:' text. This is exactly the context annotations cannot convey.

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?

Front-loads the payload definition before the workflow and constraints, and the mandatory OUTPUT CONTRACT is correctly emphasized. It is dense and somewhat repetitive on the marketplace rule (repeated in both description and schema), but nearly every sentence carries operational weight.

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?

With no output schema, the description compensates by enumerating the returned data fields, stating what is absent (listing facts), and flagging the conditional 'Account notice' response. An agent has everything needed to call it and interpret the result.

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, but the description adds genuine meaning beyond the schema: the marketplace code must be solicited from the user once and reused for every later call, must never default to US, and determines the currency of all monetary fields. The asin parameter itself adds no detail beyond the schema.

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?

States a specific verb and resource ('Full raw data for a single Amazon product by ASIN') and enumerates the exact payload (price, sales/revenue, reviews, rating, LQS, sellers, history). It explicitly distinguishes itself from the sibling amzscout_advanced_product_data, so an agent can route correctly without opening either schema.

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?

Gives an explicit analytical workflow ('audit the product like a sourcing analyst — demand trend, pricing direction, competition, listing quality, then GO/NO-GO'), names the complementary sibling to call alongside it, and prescribes the marketplace-resolution behavior (ask once, reuse, never assume US). Alternatives and conditions are spelled out rather than implied.

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