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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the description's added value is the payment model: $0.001 USDC per successful call via x402 on Solana, plus a same-function HTTPS endpoint. Disclosing that calls are metered/paid is exactly the kind of auth/cost context annotations cannot express.

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, then domain bounds, then pricing/endpoint. Every sentence carries information, though the pricing and alternate-endpoint clause densifies the tail slightly.

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 arithmetic function with no output schema, the description supplies semantics, worked examples, valid input range, cost, and an alternate transport. Nothing an agent needs to call it correctly 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?

The schema has 0% description coverage on `n`, but the description compensates by stating the domain ('n runs from 1 to 7560') and illustrating the mapping with concrete input/output pairs. That is more than the bare integer/min/max in the schema conveys.

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?

States a precise verb+resource relationship ('least highly composite number >= n') and immediately grounds it with four worked examples, including the boundary case 5041 -> 7560. The 'next' semantics inherently distinguish it from membership-test siblings like highly_composite or counting siblings like highly_composite_count.

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: given n, return the successor highly composite number. However, it never explicitly names when to reach for this versus highly_composite (membership) or highly_composite_count, leaving that inference to the agent.

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