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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds meaningful behavioral context: bounded serving tables only, no raw-table fallback, no wildcard/substring scan, and a hard 42-day window. The mention of 'lookup_type and lookup_key prefix' references fields not present in the schema or the view enum, which is mildly confusing.

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 tight sentences: purpose first, then view routing, then constraints. Every sentence carries load, though the 'lookup_type and lookup_key prefix' phrase adds noise without a corresponding parameter.

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 an output schema present, return values need no explanation, and 14 parameters are fully covered in the schema. The description completes the picture with view requirements and the 42-day bound; the only gap is the unexplained 'lookup views' terminology that does not match the enum values.

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 every parameter is already documented individually; baseline is 3. The description adds cross-parameter conditionality (which view demands which of search_term/asin) and the date-span rule, but does not extend beyond what the schema largely establishes.

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 (Return) and resource (Amazon Brand Analytics Search Terms facts) and enumerates the three serving views with their grain, which an agent can map to the view parameter. It does not explicitly distinguish itself from the sibling get_search_terms, but the purpose is unambiguous.

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 concrete selection rules: top_terms for term-grain ranks, term_products requires one exact search term, asin_terms requires one exact clicked ASIN, plus the 42-day partition constraint and no-wildcard limitation. It lacks explicit when-to-use vs sibling search tools, but the within-tool routing guidance is strong.

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