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

Annotations already cover safety (readOnlyHint, idempotentHint, destructiveHint=false), and the description adds genuinely new context: a per-success price of $0.001 USDC via x402 on Solana and an equivalent HTTPS endpoint. That cost/auth detail matters for an agent deciding whether to call. The return type (presumably a boolean) is only implied, not stated.

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?

Front-loaded predicate, then a short example list, then domain, pricing and transport in single clauses. The ten-number example list is slightly long but directly disambiguates the predicate, so every sentence earns its place.

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 one-parameter boolean predicate with no output schema, the description covers semantics, range, cost, and an alternate transport. The only real gap is the unstated return shape and the lack of contrast with the `automorphic` sibling.

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 carries the burden and does so adequately: it explains that `n` is the base whose cube is examined and gives the 1–10000 range, mirroring the schema min/max. It stops short of specifying behavior at the boundaries or input type beyond the range.

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 definition gives a precise predicate (whether n^3 ends with n) plus worked examples of satisfying and non-satisfying inputs, so the computed property is unambiguous. It does not differentiate from the sibling `automorphic` (the analogous n^2 case), so an agent choosing between the two must infer the distinction from the names alone.

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 valid domain ('n runs from 1 to 10000') is stated, which tells an agent when the call is in scope. However, there is no guidance on when to prefer this over the near-identical `automorphic` sibling, nor any when-not-to-use framing.

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