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

Annotations already declare readOnly/idempotent/destructive=false, and the description adds real cost and access context: $0.001 USDC per successful call via x402 on Solana and an equivalent HTTPS endpoint. That pricing, which is not captured anywhere in annotations, is material for an agent deciding whether to invoke. It stops short of describing the return shape.

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 with the definition, then examples that disambiguate the edge case, then the range and pricing. Every sentence carries information; 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?

For a single-parameter boolean predicate with no output schema, the description supplies the definition, domain, and cost. The only gap is an explicit statement that it returns a boolean.

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%, but the description compensates partially by stating n's domain ('n runs from 1 to 20000'), which is actually duplicated by the schema's min/max. It clarifies that n is the integer being tested via the definition, but adds no format/semantic detail beyond the schema bounds.

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 gives a precise mathematical definition ('abundant, but not semiperfect') plus worked examples (70, 836 weird; 12 not), so an agent knows exactly what predicate is computed. It does not explicitly distinguish itself from the many sibling number-property tools (abundant, semiperfect, abundancy), which keeps it from a 5.

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 only implied: the definition and examples let an agent infer this is a yes/no test for a single integer in 1..20000. There is no explicit statement of when to prefer this over sibling predicates like semiperfect or abundant, and no exclusions.

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