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

With no annotations, the description carries the full transparency burden. It discloses that the call is free, returns scope and price, and explains tier pricing and category granularity. It does not explicitly state side effects or confirm it is read-only, but 'FREE' and 'Return the scope and price' strongly imply a non-mutating quote operation. Some behavioral details, such as whether the quote is binding or expires, are absent.

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 concise and front-loaded with the most important facts: free, returns scope/price, tier options. The pricing list is necessary and compact. It could be slightly more structured, but every sentence earns its place and there is no 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?

The tool has an output schema, so return-value details are not required. With no annotations and no usage guidance, the description covers pricing and scope but omits when-to-use guidance relative to the sibling tools and some edge-case policy (e.g., what happens if categories exceed the local tier limit). It is adequate for a straightforward quote tool but has clear gaps.

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 0%, so the description must compensate. It adds real semantics for 'tier' by listing all allowed values with prices and category allowances, and clarifies that categories are separate units of work. 'business_name' and 'categories' are given context through 'business NAMED in AI answers' and 'given categories.' Minor gaps remain around category format and tier limits, but the description does substantial work beyond the bare 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 opens with a specific verb and resource: 'Return the scope and price to get a business NAMED in AI answers for the given categories.' It clearly explains what the quote covers and even defines categories as separate data-engineering units. This distinguishes it from the audit and purchase sibling tools without needing to name them.

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 usage: it is a free quote request for pricing and scope before engaging. However, it does not explicitly say when to use this tool instead of audit_business_visibility or purchase_engagement, nor does it state prerequisites or when not to use it. The phrase 'FREE' and the pricing details hint at the pre-purchase context but leave routing to inference.

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