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

The annotations already provide readOnlyHint=true and destructiveHint=false, so the description's behavioral burden is reduced. It usefully adds that the calculation is a sales-weighted split of campaign-level SB spend, which is a meaningful methodology detail. It does not disclose output granularity, zero-attribution handling, or currency behavior, but these are less critical for a safe read-only tool.

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 a single concise sentence that introduces the core concept and immediately adds the key methodological qualifier in parentheses. Every word earns its place, and the most important scoping information is front-loaded.

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 simple read-only attribution tool with optional parameters, the description is largely sufficient. It clearly defines the result: per-ASIN SB cost attribution. It omits the expected output shape and potential edge cases like whether ASINs with zero attributed spend are included, and no output schema exists to pick up that slack.

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?

The input schema already describes date_from, date_to, and seller_connection_id, so 3 of 4 parameters have coverage. The description itself adds no parameter-level guidance, and the currency parameter's meaning remains undocumented. Since all parameters are optional and defaults are specified in the schema, the description does not need to compensate heavily.

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 concrete deliverable: per-ASIN Sponsored Brands cost attribution, with the clarifying detail that it is the sales-weighted split of campaign-level SB spend. Although there is no explicit verb like 'computes' or 'returns', the noun phrase is unambiguous. It is distinguishable from generic P&L/PPC siblings by naming Sponsored Brands, per-ASIN scope, and the attribution methodology.

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 intended use is implied: an agent would call this when it needs Sponsored Brands campaign spend allocated to individual ASINs. However, there is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. Among a large sibling set, the agent must infer routing purely from the description.

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