topai_google_ai_overview

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so 'Stateless, read-only execution' largely restates structured data; the 'stateless' qualifier is the only genuinely additive bit. The description does not mention auth, rate limits, or failure modes. No output schema exists, so the enumerated return fields carry some behavioral weight, but the safety profile is already annotation-covered.

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 sentences, front-loaded with what is extracted, then usage, then the exclusion, then the safety note. Every sentence earns its place with no redundant preamble or filler.

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?

No output schema exists, and the description compensates by naming the three returned artifacts (synthesis text, cited URLs, organic SERP count), which is enough for a stateless read tool taking a single required query. Minor gaps remain around null/empty-result behavior and localization semantics, but the essentials are covered.

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 coverage is 100%, so all three parameters (query, country, language) already have descriptions including defaults ('us', 'en'). The description adds no syntax, format, or constraint detail beyond the schema, which is the expected baseline when the schema does the heavy lifting.

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 (Extracts) and resource (Google AI Overview), and enumerates the exact payload returned: synthesis text, cited source URLs, and organic SERP count. It also differentiates itself from the sibling topai_ai_web_search by name, so an agent can route without opening either 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?

Gives explicit positive triggers (GEO audits, citation tracking, analyzing Google AI summaries) and an explicit exclusion with the alternative to use instead ('Do not use for general fast web search when AI Overview citation tracking is unnecessary (use topai_ai_web_search instead)'). Nothing is left to inference.

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