What people searched to find this business

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

Annotations already mark readOnlyHint=true and destructiveHint=false, but the description adds high-value behavior: low-volume terms are suppressed with impressions=null and below=<threshold>, counts are unique users not impressions, only ~12 months of history, read-only with 0 credits, and requires connected profile. This is exactly the kind of context that prevents misuse.

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 dense paragraph but every sentence adds value: purpose, contrast with sibling, suppression warning, unit clarification, retention, and operational requirements. It is front-loaded with the core purpose. Not perfectly structured (could use bullets) but appropriately sized for the complexity.

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?

Despite no output schema, the description explains the meaning of key fields (impressions=null, below) and the uniqueness of the data. All operational prerequisites (connected profile, credits, read-only) are stated. With 4 optional params and rich annotations, nothing critical is missing.

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%, so all four parameters are documented. The description adds no new parameter-specific semantics beyond the schema (e.g., it doesn't explain limit or months more than the schema does). Baseline 3 is appropriate since schema carries the semantic load.

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 states exactly what the tool returns: the actual search terms users typed before the business listing appeared. It explicitly contrasts with sibling google_business_insights, distinguishing 'HOW MANY' vs 'WHICH WORDS', making the purpose unambiguous and differentiated.

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 names the direct use case (input to Google Ads keyword set, page titles, profile description) and explicitly contrasts the sibling tool google_business_insights, telling the agent which to use when. It also gives critical reporting guidance for suppressed terms, which is a when-to-use instruction in disguise.

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