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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral detail by disclosing that results are per-marketplace and include seller count, ASIN count, observed buybox days, and control score. This goes beyond what annotations provide, though it does not explain how 'control score' is defined.

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 three sentences with no filler. The core purpose and output metrics are front-loaded, followed by concrete example queries. Every sentence adds value, and the structure makes it easy for an agent to quickly understand when and how to use the tool.

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 has 10 parameters, low schema coverage, and no output schema. The description provides a clear high-level purpose, example usage, and a general list of returned metrics, which is sufficient for selecting the tool and calling it with just the required brand parameter. However, it leaves the optional filter semantics and the full output structure undefined, so it is only minimally complete for more advanced invocations.

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 only 20%, and the description does little to compensate. The brand parameter and marketplace_id_in are documented in the schema, but the eight numeric filter parameters (min/max seller count, ASIN count, control score, observed buybox days) are undocumented in both schema and description. The description mentions the output metrics but not how the filters behave or whether they apply per-marketplace.

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 states a specific verb ('Check whether'), a specific resource ('a brand'), and the exact marketplaces covered (Amazon US, Amazon UK, Walmart). It also names the output metrics, making the tool's function unmistakable and distinguishing it from sibling tools like keyword_cross_marketplace or xmkt_pricing_compare.

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 gives concrete user-query examples ('does this brand sell on Walmart', 'is this brand on Amazon UK') and says to use it for 'any multi-marketplace brand question.' This provides clear when-to-use context, though it does not explicitly discuss when not to use it or name alternative tools.

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