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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, covering the core behavioral safety profile. The description adds context about the data nature (aggregated, verbatim quotes, sentiment trends) but does not disclose additional behavioral details like pagination, rate limits, or auth requirements. With annotations present, the bar is lower, and the description adds some value beyond the annotations.

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 compact at two sentences, front-loads the 'Voice of Customer' brand, then lists the included data types and use cases. It is efficient with no filler, though it could be slightly more structured with a verb-led opening.

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?

The tool is low complexity with one optional parameter, and the schema covers that parameter. No output schema exists, but the description enumerates the major output categories ('review topics, sentiment trends, verbatim quotes + category return reasons') and gives concrete use cases. This is sufficient for an agent to select and invoke the tool correctly, though it does not describe the exact response structure.

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% and the schema already explains the single optional 'asin' parameter in detail ('Optional — one ASIN for its detailed feedback; omit for a catalog overview'). The tool description does not add parameter-level detail beyond what the schema provides, so the 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?

The description clearly identifies the resource: 'Amazon's aggregated review topics, sentiment trends and verbatim quotes + category return reasons.' It distinguishes itself from siblings by focusing on customer feedback/reviews rather than campaigns, sales, or keywords. However, it lacks an explicit action verb like 'retrieves' or 'gets,' so it stops short of the strongest purpose statement.

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 phrase 'Use for "reviews", "why did my rating drop"' provides explicit guidance on when to invoke this tool. It gives clear use cases but does not mention when not to use it or name alternative sibling tools, so it lacks exclusions but still offers clear context.

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