search_brand

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

No annotations are provided, so the description carries the disclosure burden. It states the search scope ('across all brand topics') but does not describe matching behavior, result ordering, or return shape; for a read-only keyword search this is adequate but minimal.

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?

Two short sentences, with the core purpose front-loaded and examples in the second sentence. No filler or repetition of schema details.

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 one-parameter search tool with no annotations or output schema, the description covers the core purpose and gives usage examples. It stops short of describing what the result set contains or whether matching is partial/case-insensitive, but these are not blockers for an agent invoking the tool.

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 schema already describes the single `query` parameter ('Search terms.'), so coverage is 100%. The description adds value by illustrating appropriate query values ('focus color', 'hover', 'disabled button'), making the parameter's expected semantics concrete.

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 uses a specific verb–resource pair ('Keyword search across all brand topics') and gives concrete example queries. This clearly separates it from siblings like list_brand_topics (enumeration) and get_brand_topic/get_color (targeted retrieval).

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 indicates when to use the tool via example questions ('Good for questions like...'), giving an agent a clear match signal. It does not explicitly state when to prefer a sibling tool, so exclusions are left implicit.

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