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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful semantic context about the data being aggregate Brand Analytics versus customer-level identity, but omits things like data freshness/ingestion lag, auth requirements, or how periods are synced.

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 with no filler; the core purpose and period scope are front-loaded, and the granularity caveat is appropriately placed last. Efficient, though slightly more repetition of schema-level detail than strictly necessary.

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 and rich annotations, the description need not explain return shapes, and it adequately conveys the data's nature and scope. It leaves minor gaps around usage routing and freshness behavior, but nothing an agent needs to invoke it correctly is absent.

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 (asin, period, limit, offset, sort_by, date bounds, includes) is already documented in the schema. The description restates period values and metric meaning but adds no format, defaulting, or pagination detail beyond the schema, so 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+resource ("Returns Brand Analytics repeat-purchase behavior") and scope (by ASIN, week/month/quarter periods), and enumerates the returned metrics. The closing sentence distinguishes the data's granularity (aggregate vs. daily customer-level order identity), though it never names a specific sibling tool, so differentiation is implicit rather than explicit.

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 conveys context (Brand Analytics aggregate data for repeat-purchase analysis), so intended usage is inferable, but it never states when to choose this over alternatives like get_product_performance, get_brand_health, or order-level tools, nor any prerequisites or exclusions. Implied usage only.

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