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

Annotations already establish the safe-read profile (readOnlyHint true, destructiveHint false, openWorldHint false), so the description only needs to add behavior. It does: the implicit default time window and the explicit refusal to produce opportunity labels or cross-sell recommendations, which prevents an agent from misreading the output as advice. Pagination and freshness behavior live in the schema, so the remaining gap is minor.

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 sentences, no filler: the first front-loads the grain and the facts returned, the second states the default window, the third states the scope boundary. Each sentence carries distinct information.

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 12-parameter read tool with a fully described schema and an output schema in place, the description covers what structured fields cannot: the analytical grain, the default reporting window, and the deliberate absence of recommendations. Nothing an agent needs to select or invoke it correctly is missing.

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 12 parameters, so the baseline is 3. The description contributes the ASIN-pair grain and the default week semantics, which help interpret primary_asin/paired_asin and the date bounds, but it adds no syntax or constraint detail beyond what the schema already documents.

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?

Names a specific verb and resource ('Return weekly Amazon Brand Analytics Market Basket pair facts') and pins the grain precisely at primary-ASIN × paired-ASIN, then enumerates the returned facts (purchased-with rank, combination percentage, report dates, marketplace). That grain/field specificity clearly separates it from neighbors like get_purchased_products, get_repeat_purchase_behavior, and get_product_performance.

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 clear operating context — default is the latest complete Sunday-Saturday week — and an explicit scope exclusion: it does not label opportunities or recommend cross-sells. It does not name an alternative sibling or state when to reach for a different tool, so it stops short of full routing guidance.

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