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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds genuine behavioral context absent from the structured fields: complaints are ordered first, the summary reflects ALL reviews while theme extraction is limited to featured reviews on the page, and it details the returned breakdowns. It omits auth/rate-limit or failure behavior, keeping it from a 5.

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 core deliverable and keeps the reader oriented with the 'complaints come first' note up front. It is dense and packed with clauses, but nearly every sentence conveys actionable output/usage information rather than filler.

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 present, the description carries the burden of explaining returns, and it does so thoroughly (topics, sentiment labels, mention counts, positive/negative totals, star breakdown, quotes). An agent has enough to know what it will get back.

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%, so both parameters (asin, marketplace) are fully documented in the schema. The description adds no format, validation, or marketplace-specific meaning beyond that, 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?

States a specific verb (mine/find) and resource (complaints on an Amazon product), and immediately names the concrete payload: Amazon's 'Customers say' topic summary with counts and quotes. This is clearly distinguishable from siblings like amazon_product or amazon_listing_audit.

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?

Provides explicit intent guidance ('Use on competitors to find product improvements and listing angles') and an internal usage rule ('Lead with the negative and mixed topics'). It does not name an alternative tool or state when NOT to use it, so it falls short of a 5.

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