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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuinely useful behavior the annotations lack: computation happens on the server, the result is 'free', and it is derived from source URLs rather than brand names, which prevents misreading the output. It does not discuss failure modes when searches are still running, but wait_seconds in the schema partly covers that.

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?

Dense and front-loaded: the compute-and-return semantics come first, then cost, then the routing sentence. A few fragments ('Free.', 'Based on source URLs, not on brand names.') are short but each carries a real disambiguation point, so little is wasted.

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?

With no output schema, the description carries the return-value burden and does so by enumerating per-domain metrics and the AI-Overview count. Combined with annotations covering the read-only profile and a fully documented schema, an agent has everything needed to call it correctly.

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 100%, so ids, top, and wait_seconds are already fully documented in the schema. The description adds no syntax, ordering, or constraint detail beyond that (e.g. it never mentions the 500-id cap or the 55s wait ceiling), so the baseline of 3 applies.

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?

States a specific verb and resource — computes which domains Google cites in AI Overviews for already-created google_search IDs — and enumerates the returned aggregates (keyword count, mentions, keywords, best position). An agent can distinguish it from get_serp_results or list_searches without opening any schema.

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?

Explicitly frames the use case as 'best tool to answer which sites Google cites... one small answer instead of every SERP,' which routes the agent away from fetching full SERPs. It stops short of naming the sibling by name or stating when-not-to-use conditions (e.g. pre-search vs. post-search), so it is clear context rather than a complete decision rule.

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