AI assistant brand visibility

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

Annotations already declare readOnly, openWorld and non-idempotent, so the safety profile is covered; the description goes further by disclosing runtime (1-3 minutes) and a concrete per-answer pricing model ($0.05/$0.04 plus $0.50 per report), which is real decision-relevant behavior for an agent. It does not mention auth or rate-limit characteristics.

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 definition is front-loaded with purpose and output contents before cost and timing, and every sentence carries information. It is somewhat long, but the length is justified by the number of returns and pricing details it must convey.

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?

There is no output schema, so the description carries the full burden of explaining returns, and it does so by enumerating mention, rank, citation, competitors, sentiment, snippet and sources. Combined with timing and pricing, 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 coverage is 100%, so the baseline is 3, but the description adds value by naming the engines behind the enum values and clarifying the metering unit ("each prompt on each engine is one answer checked"), plus flagging the extra charge tied to create_report.

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 states a specific verb and resource: ask AI assistants the customer's questions and check whether they mention/cite the brand, and it enumerates the returned signals (mention, rank, citation, competitors, sentiment, snippet, sources). It is very clear on its own, but it never distinguishes itself from the sibling check_ai_overview_citations, which sounds closely related.

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?

"Use it for AI search visibility and share-of-voice tracking" implies the usage context but gives no explicit when-not condition and names no alternative tool, even though check_ai_overview_citations sits in the same sibling list. The cost/latency notes help an agent decide to call it, but routing guidance is absent.

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