jackpotkeywords_aeo_scan

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

With no annotations, the description fully discloses behavior: it queries Gemini, reports citation status per query, lists top sources, costs $1.00, refunds on failure, and has 30-120s latency. This covers all key behavioral traits necessary for an AI agent to decide and invoke correctly.

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 two concise sentences, front-loading the core purpose and following with essential details. Every sentence adds value, and there is no redundant information.

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?

Given the tool's complexity (cost, latency, failure handling, query logic), the description covers all key aspects: what queries are used, what the output reports, cost structure, failure refund policy, and expected latency. No output schema exists, but the description adequately describes the return format.

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%, and the description adds meaningful context for the optional 'productContext' parameter, explaining when to use it and its cost implications. For the required 'url' parameter, the description provides an example URL, adding slight value beyond the schema.

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 it runs an AI-visibility scan for a product URL, listing specific actions (10 buyer-intent queries, reporting per query). It explicitly names the resource (product URL) and distinguishes from sibling tools by its unique scanning function.

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 implies the tool's use case for checking AI visibility, but it does not explicitly state when to use this tool versus the sibling tools (credit_balance, recommend) nor provide exclusion criteria. The context is clear from the purpose but lacks explicit guidance.

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