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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description only needs to add context beyond that. It adds that the endpoint is free, has zero parameters, and returns current pricing, which is useful operational context not present in annotations. The existence of an output schema covers the return-shape burden, so the lack of return-format detail is not a gap.

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 compact and front-loaded: the core purpose comes first, followed by two labeled usage directives. Every sentence adds information and none repeat schema or annotation content.

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?

For a zero-parameter, read-only endpoint with an output schema and clear sibling context, the description covers purpose, scope, supported types, and usage boundaries. Nothing an agent needs to decide to call this tool is missing.

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?

With zero parameters and 100% schema coverage, there is nothing semantic to document. The description reinforces this by explicitly stating 'zero parameters,' so an agent knows no hidden inputs are expected.

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—'Retrieve'—and a precise resource: current x402 pricing per 1,000 CAPTCHA solves, enumerating supported types. It is immediately distinguishable from siblings like solve_captcha because it frames the tool as an information endpoint, not a solving tool.

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?

It explicitly states when to use the tool ('Check current rates and atomic USDC requirements before calling solve_captcha') and when not to ('Do NOT use to submit or solve CAPTCHA challenges'). It names the relevant sibling solve_captcha, giving an agent clear routing logic.

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