genai_query_insights

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by revealing that detection is heuristic, based on patterns like prompt verbs and conversational phrasing, operating on regular query-level performance data, and that results are an undercount rather than official. It does not describe return format or side effects, but the read-only nature is reasonably implied by 'Detect'.

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 two sentences with no filler. The first sentence front-loads the core purpose, and the second adds critical methodology and limitations. Every clause earns its place.

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 there is no output schema and no annotations, the description provides enough context to select and invoke the tool: purpose, scope, method, data source, and limitations. The main gap is that it does not describe the response shape or whether results are grouped or detailed, but the current description is still sufficiently complete for a heuristic insights 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 input schema has 100% parameter description coverage, so the schema already explains days, engine, siteUrl, includePages, and minImpressions. The description does not add meaningful parameter-level semantics beyond the schema; it mentions matching patterns but does not map those patterns to specific parameters. Baseline 3 is appropriate.

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 opens with a specific verb ('Detect') and a precise resource ('likely generative-AI / AI-Mode / conversational fanout queries across Google and Bing'). This clearly distinguishes it from sibling tools like analytics_query or compare_engines, which target general query analytics or engine comparison rather than genAI-specific detection.

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 gives clear context for when this tool is appropriate: when you need to detect genAI-style queries and are aware that public APIs lack citation data. It also provides an important exclusionary caveat ('it is an undercount, not an official report'). However, it does not explicitly name alternative tools or state when not to use it in favor of regular analytics tools.

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