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 meaningful context beyond that: non-cycle inputs return 0, open chains are rejected, the valid input range, and pricing/payment details via x402 on Solana.

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: it defines the result, gives examples, states edge-case behavior, then supplies practical invocation details. Every sentence adds useful information without redundancy.

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 mathematical function with no output schema, the description is complete enough: it explains the return value, non-cycle and open-chain behavior, input range, and access/payment details. No critical information for correct invocation 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?

Schema description coverage is 0%, but there is only one parameter and the description compensates with concrete input-output examples (6 gives 1, 220 gives 2, 12496 gives 5, 25 gives 0) plus the valid range. It does not define 'aliquot cycle' in depth, but the purpose statement supplies enough meaning for the parameter.

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 precisely states what the tool returns: the length of the aliquot cycle containing n, with 0 for non-cycle inputs. It is clear and specific, though it does not explicitly distinguish itself from siblings like sociable, sociable_chain, or sociable_min.

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 purpose: compute the aliquot cycle length for a given n. The description clarifies edge cases such as open chains being rejected and non-cycle inputs returning 0, but it gives no explicit guidance on when to choose this tool over related sibling tools.

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