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

Annotations already mark the tool as read-only, idempotent, open-world, and non-destructive. The description adds useful operational context beyond the annotations: pricing, successful-call charging, x402/Solana payment, and an HTTPS endpoint.

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 front-loaded with the core purpose and then adds examples, range, and payment/endpoint details. It is generally efficient, though the five example mappings are slightly more verbose than strictly necessary.

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 mathematical query, the description covers purpose, range, examples, and payment/endpoint context. It does not explicitly define Hamming numbers or state the return type, but the examples make the count output clear.

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 the burden for the single parameter. It successfully clarifies that n is an upper bound and gives concrete examples mapping n values to counts, though the numeric min/max range largely repeats the schema.

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 states a specific verb-and-resource purpose: counting Hamming numbers at most n. It is clear enough to distinguish this from related sibling tools such as hamming_nth or hamming_next, but it does not explicitly name or contrast those alternatives.

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 description gives examples and a valid n range, but it does not explain when to use this tool versus related siblings like hamming, hamming_nth, or hamming_index. There is no explicit when-to-use or when-not-to-use guidance.

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