get_brand_vs_nonbrand

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

While annotations cover safety (read-only, idempotent), the description adds valuable behavioral context by detailing the specific data points measured (clicks, positions, etc.), which enhances the agent's understanding of the tool's output scope.

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 structure is excellent, presenting the high-level purpose first, followed by a clear, well-organized list of arguments and their descriptions. Every part of the text is useful.

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 that the input schema was not descriptive, the description successfully covered all necessary technical and semantic details required to make the tool callable correctly. It defines defaults and complex input formats thoroughly.

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?

Since schema coverage was 0%, the description provided vital semantic meaning for all parameters. It clarified that `site_url` is an exact property (with defaults) and provided a concrete example and format for `brand_terms` ('acme,acme corp,akme').

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 defines the tool's function as splitting traffic into branded vs non-branded segments. It explicitly lists the metrics returned: share of clicks/impressions, CTR, position, and top queries.

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 tool describes *what* it does but provides no explicit guidance on *when* to use it versus the multitude of available sibling analytics tools. Usage is implied by its specific function rather than stated definitively.

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