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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral details: generic promo/code words are ignored, exact brand matches are prioritized, only catalog records are returned, unknown queries yield an empty array, and product/region do not establish eligibility. These are valuable clarifications beyond the annotations.

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 compact and front-loaded, with each sentence contributing meaningful information. It covers matching behavior, ordering, return type, empty results, and caveats without unnecessary filler. This is an efficient, well-structured description.

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 search tool with an output schema and clear safety annotations, the description covers the most important behavioral aspects: what is searched, matching rules, ordering, empty results, and non-eligibility caveats. Minor gaps remain around pagination and how limit/offset interact with the result list, but these are partly addressed by the schema and output schema.

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 coverage is 60%, with query, region, and product described in the schema. The description adds context by noting matching behavior and that product/regional applicability is caveated, which enriches region and product semantics. However, it does not clarify limit or offset semantics, and it does not fully compensate for the missing schema descriptions.

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 clearly identifies the action ('Search') and the resources: brand aliases, categories, and benefits. It adds behavioral specifics such as exact brand matches first and catalog-record-only returns, making the tool's purpose easy to grasp. It does not explicitly distinguish itself from siblings like list_brands or get_code, so it stops short of a 5.

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 implies when to use the tool: it is for searching brand aliases, categories, and benefits, and generic promo/code words are ignored. However, it gives no explicit when-not-to-use guidance or references to sibling tools such as get_code or list_brands. Usage context is mostly implied rather than stated.

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