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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is partly covered, and idempotentHint=false is consistent with the description's warning that repeated calls may charge again. The description adds genuine behavioral value by disclosing the credit cost per successful call and flagging returned data as untrusted, which annotations do not 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?

Three short sentences, front-loaded with the purpose before cost and safety notes. Each sentence carries distinct information (capability, cost, trust), with no filler or repetition.

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 64-parameter tool with no output schema, the description covers capability, cost, and trust but says nothing about what the response looks like (e.g., that it returns a list of product records with the requested fields). The 100% schema coverage compensates for the parameter gap, leaving the return-shape omission as the main shortfall.

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 100% across all 64 parameters, so the schema carries the full parameter semantics. The description only loosely groups the filter families (category, sales, price, review, seller), adding categorization but no syntax or constraints beyond what the schema already documents. Baseline 3 applies.

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 clear verb+resource (research products) and enumerates the filter dimensions it supports (category, sales, price, review, seller). However, it does not differentiate itself from near-neighbors like amazon_market_research, amazon_market_goods, or amazon_product_node, so an agent cannot tell them apart without opening schemas.

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 gives no when-to-use context, no prerequisites, and no exclusions relative to the many sibling research tools. The agent gets filter vocabulary but no guidance on which research endpoint to pick or when this tool is the right choice.

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