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

With no annotations present, the description carries the full burden of behavioral disclosure. It clearly discloses the pay-per-call cost ($0.04 USDC on Base via x402), the required payment-signature header, and the specific error behavior when that header is missing (the error data carries payment terms). This is valuable beyond the schema. It does not mention side effects or data handling, but for a generative tool this level of transparency is adequate.

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 three sentences, each delivering distinct information: purpose and output, pricing, and error handling. It is front-loaded with the action, contains no filler, and every sentence earns its place. This is an model of conciseness.

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 two optional parameters, no output schema, and no annotations, the description covers the essentials: what it generates, output format, and the payment/error contract. It does not explicitly state that a query is expected despite being optional, nor does it describe the exact structure of the categories, but these are minor gaps for a simple generative tool with a clear purpose.

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%, meaning both 'query' and 'context' are adequately documented in the schema itself. The tool description adds no additional parameter semantics; it only restates that it generates questions. Per the calibration, a baseline of 3 is appropriate when the schema already handles parameter meaning.

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 uses a specific verb 'Generate' and resource 'case study discovery questions', and specifies the output: '10 open-ended questions organized by category.' This clearly conveys what the tool does. However, it does not explicitly distinguish it from the sibling tool 'generate-testimonial-questions', though 'case study' vs 'testimonial' implies a domain difference.

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?

There is no guidance on when to use this tool versus alternatives such as generate-testimonial-questions or other content-generation tools. The description mentions a payment prerequisite, which is a calling condition, but it does not explain the appropriate use case or exclusions. An agent would have to infer usage solely from the tool name.

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