ai_overviews_impact

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

With no annotations, the description carries the full burden. It discloses error handling behavior (returns error dict on HTTP 400/403 instead of raising) and the specific dimension used. This adds useful behavioral context beyond what annotations would provide, though it does not mention read-only nature or side effects.

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 three sentences, front-loading the purpose, then adding technical detail and error handling. Every sentence adds value with no waste. It is efficiently structured for quick agent scanning.

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?

While the description covers the tool's purpose, technical approach, and error behavior, it lacks critical parameter details and does not mention the output structure (though an output schema exists). Given the tool's moderate complexity (3 params, 1 required) and no annotations, more completeness would be beneficial.

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 description coverage is 0%, yet the description provides no explanations for the three parameters (days, site, limit). The agent must infer meaning from parameter names alone, which is insufficient. Baseline for no param info is low, and the description fails to compensate.

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 function: 'Get queries where AI Overview appearance data is available.' It specifies a unique resource (AI Overview data) and uses a specific verb. Among siblings, none target AI Overviews, making it easily distinguishable.

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 explains the technical approach (searchAppearance dimension, dataState=all) but does not provide explicit guidance on when to use this tool vs. alternatives like get_search_analytics. The context of siblings implies it is for AI Overview-specific data, but no direct usage boundaries are given.

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