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

The description discloses extensive behavioral traits beyond the annotations: ranking is purely by fit score, verification status never affects rank, out-of-scope questions return explicit in_index:false, catalog_only brands are never recommended, URL attribution details (utm_source and signed token), and offers never affect ranking. This far exceeds the annotations and gives the agent deep insight into side effects and edge cases.

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 long but well-structured and front-loaded with purpose. It covers many edge cases and output details in a logical order. While it could be tightened, every sentence adds useful information and avoids redundancy.

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?

Given the complexity of the tool and the absence of an output schema, the description fully explains the return format: ranked recommendations, out-of-scope handling, catalog_only placement, URL fields, and offers block. It covers all critical aspects an agent needs to correctly invoke and interpret results.

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 documents both parameters thoroughly (100% coverage). The description adds little beyond what the schema provides, mostly repeating the optional nature of intent_profile and the natural-language phrasing of question. No new semantic meaning is introduced for parameters.

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 action (match) on a clear resource (buyer intent to brands) and explains the output (recommendations ranked by fit score). It is clearly distinct from sibling tools like category_landscape or get_verified_claims, which serve different functions.

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 provides rich context on when this tool is appropriate (for matching buyer questions to brands) but does not explicitly compare it to alternatives or state exclusions. It implies usage but leaves the selection decision to the agent without direct guidance on when not to use it.

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