google_serp_ai_overview: GET /

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 mention the token's 4-minute validity and that the content is lazy-loaded, which adds useful context. However, it does not explicitly state that the operation is read-only or that it has no side effects, nor does it address error handling for expired tokens. The 'fetches' verb implies a GET, but for a tool with zero annotation coverage, this is a moderate gap, earning a 3.

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 front-loaded with the purpose and then provides necessary detail. It is about three sentences long and each sentence adds value—how it works, what it returns, and when to use it. The use-case list is slightly verbose but still relevant for agent decision-making. It earns a 4 for being well-structured without unnecessary fluff.

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?

For a simple tool with one parameter, the description covers the essential context: the source of the token, its validity, the output contents, and typical use cases. It does not explain error behavior or pagination, but given the low complexity and absence of an output schema, it is sufficiently complete for an agent to call it correctly. A score of 4 reflects this adequacy.

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 covers the only parameter (pageToken) with a description that already states its origin and validity. The tool description repeats this information without adding new meaning or providing additional guidance on how to obtain or handle the token. With schema description coverage at 100%, the baseline is 3, and the description does not exceed it.

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 uses a specific verb ('fetches') and resource ('lazy-loaded Google AI Overview block'), and clearly distinguishes this from sibling tools by focusing on the follow-up nature. It explicitly states what it returns (AI-generated answer text, referenced source URLs, expanded subtopic sections), so an agent can understand its unique purpose without ambiguity.

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 clearly states 'Use as a follow-up call to Google SERP', which gives a clear context for when to invoke it. It does not explicitly name alternatives or provide exclusions, but it makes the usage pattern (follow-up after obtaining a pageToken) explicit enough to differentiate from initial search calls. A score of 5 would require explicit alternatives, so 4 is appropriate.

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