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

With no annotations, the description carries the full burden. 'Check whether' does convey a non-mutating boolean predicate, which is meaningful, but it says nothing about input handling (numeric vs string), behavior on malformed input, or the shape of the result. Adequate but thin.

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?

Two short sentences, front-loaded with the operation. The trailing fragment 'Provide value.' is redundant filler that slightly weakens an otherwise tight definition.

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 trivial predicate tool this covers what and why, but with no output schema it leaves the return shape and input-type expectations unstated, and it gives no disambiguation against the numerous sibling validators.

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 100% but the schema's own text ('Value to process') is uninformative, and the description adds no extra meaning beyond a dangling 'Provide value.' Baseline 3 applies since the schema formally documents the single 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 names a specific verb and resource ('Check whether a number passes the Luhn checksum') and clarifies the domain ('used for credit cards and IDs'). An agent can grasp the operation, though it does not explicitly distinguish itself from overlapping siblings like x402-credit-card-validate or x402-is-credit-card.

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 phrase 'used for credit cards and IDs' hints at context, but there is no explicit when-to-use, when-not-to-use, or named alternative among the many sibling validators (x402-luhn-adjacent, x402-credit-card-validate). The agent must infer routing on its own.

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