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

Annotations already declare read-only, idempotent, open-world, non-destructive behavior. The description adds useful behavioral context beyond annotations: the valid input range, the $0.001 USDC per successful call pricing model, and the alternative HTTPS endpoint. It does not explicitly state the return value, but 'Whether' strongly implies a boolean result.

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 compact. The examples and pricing/endpoint details are useful, though the input range repeats the schema's min/max constraints.

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 simple one-parameter predicate with annotations and no output schema, the description covers the mathematical condition, examples, input range, cost, and endpoint. The main remaining ambiguity is the exact return type, though 'Whether' implies 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 description coverage is 0%, so the description must carry parameter meaning. With only one parameter, it clearly places n in the formula sigma(n) = 3*n and states the valid range 1 to 100000, which is enough to call correctly, though it does not define sigma notation.

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 predicate, 'Whether sigma(n) = 3*n', and examples (120 and 672 are triperfect) that make the resource clear. It also distinguishes the result from ordinary perfect numbers (6 and 28), though it does not route to sibling tools such as multiperfect or perfect_check.

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 predicate: call it to test whether n is triperfect. However, there is no explicit when-to-use guidance versus related siblings like perfect_check, multiperfect, or abundancy, and no when-not-to-use conditions beyond the perfect-number example.

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