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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds genuinely extra behavioral context: the 1-credit cost, the fact that it is charged even for empty pages, and the summarized return shape. No contradictions exist.

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?

Three short, dense sentences with no filler. The first sentence front-loads the core result contents, the second covers cost, and the third summarizes the return. Every phrase adds value.

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 tool with one required parameter and a fully described schema, the description is nearly complete. It states the return format, credit cost, and empty-page behavior. Minor missing context, such as potential country fallback logic, is already handled in the schema, so the definition is sufficient.

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 the baseline is 3. The description does not add parameter-level semantics beyond the schema, but that is acceptable because the schema already documents keyword, country, and confirm_quote_id in detail.

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 specifies the resource ('Google results page') and the specific output elements: top 10 organic results, SERP features, featured snippet, AI Overview, People Also Ask, and related searches. This makes the tool's purpose concrete and distinguishes it from siblings like keyword_overview or ai_overview without being tautological.

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 provides no explicit guidance on when to use this tool over the many siblings, nor any when-not-to-use conditions. The implied use case (analyze a live SERP) can be inferred, but the agent is given no decision rule or alternative tool recommendations.

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