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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful non-schema context: the 1–200000 range, the cost of $0.001 USDC per successful x402/Solana call, and the alternative HTTPS endpoint, plus partial return semantics via 'The root is 0 when n is not a Dudeney number.'

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 and the examples, range, output note, pricing, and endpoint are all relevant. It is somewhat dense in one paragraph but every sentence contributes context.

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 a simple pure-math predicate with no output schema and rich annotations, the description covers the property, domain, examples, cost, and partial return behavior. It could be more explicit about the exact return shape when n is a Dudeney number, but it is otherwise sufficient to invoke 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 0%, so the description would ideally carry more parameter detail. It restates the min/max range already encoded in the schema but does not explain units, input format, or error behavior; for a single constrained integer parameter this is minimally adequate.

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 defines the Dudeney property precisely: n must be a perfect cube whose digits sum to the cube root, with examples and the range 1–200000. This is clearly distinguishable from generic cube or digit-sum siblings, though it does not explicitly name related tools.

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?

Usage is implied by the mathematical definition and examples, but there is no explicit when-to-use or when-not-to-use guidance, nor any routing to alternatives such as cube_min, cube_sum, or digit_sum.

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