gsc_brand_nonbrand

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

No annotations are provided, so the description carries full burden. It discloses that the split is based on brand_terms and returns aggregated metrics and top queries, but lacks details on data source (GSC API), rate limits, data freshness, or error 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?

Two sentences, no wasted words, front-loaded with the tool's core purpose. Every sentence adds essential information.

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 no output schema, the description partially explains return values but lacks format details (e.g., structure of top queries) and omits prerequisites like GSC access. Adequate but not fully comprehensive for a tool with 5 parameters and no 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 100% with descriptions for all 5 parameters. The description adds value by explaining the output (aggregated clicks, impressions, CTR, position per segment, plus top queries), which goes beyond the schema's parameter-level docs.

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 ('split') and resource ('search traffic into branded and non-branded query segments') and clearly distinguishes from siblings like gsc_search_performance, which provides overall performance, and gsc_striking_distance, which focuses on near-top pages.

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 usage for brand vs non-brand analysis but does not explicitly state when to use this tool over alternatives or provide exclusion criteria. No guidance on prerequisites or context.

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