bing_branded_vs_unbranded

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

Without annotations, the description reveals only that it splits query totals into two buckets. It does not disclose how the split is computed, whether it returns counts or percentages, any effects on data, or potential rate limits. Basic behavior is present but insufficient for full understanding.

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 a single sentence plus a parameter list, front-loaded with the core purpose. Every element adds value without unnecessary detail.

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 simple parameter set and existence of an output schema, the description provides the essential purpose and parameter semantics. However, it lacks operational details like how the buckets are returned (two columns? one metric?) which would help an agent invoke it correctly. Adequate but not thorough.

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?

With 0% schema description coverage, the description adds meaning to all three parameters: date format ('YYYY-MM-DD') and defaults for start/end date, and 'Comma-separated brand regex terms' for brand_terms. However, it omits details like inclusive/exclusive date ranges or return format, partially compensating.

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 states the tool's purpose: 'Split Bing query totals into branded vs unbranded buckets.' It uses a specific verb ('split') and resource ('Bing query totals'), and distinguishes from sibling gsc_branded_vs_unbranded by specifying 'Bing'.

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 branded vs unbranded analysis but does not explicitly state when to use it versus alternatives like gsc_branded_vs_unbranded or other Bing tools. No guidance on prerequisites or exclusions.

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