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x402node_validate_creditcard

Validate credit card numbers using Luhn algorithm. Detect card brand (Visa, Mastercard, Amex, Discover, etc.) and return validity with masked number.

Instructions

Credit card validator / Luhn algorithm check / card number verification / card type detector / Visa Mastercard Amex Discover Diners JCB UnionPay brand identifier / PAN validation. Validate credit card number via Luhn algorithm and identify card brand. Returns validity, card type, masked number. No payment processing, validation only.

Price: unknown on Base (auto-paid in USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cardYesCredit card number (required, digits or with spaces/dashes)
Behavior4/5

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

Discloses algorithm (Luhn), output (validity, card type, masked number), and non-payment nature. No annotations provided, so description carries full burden and does well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is verbose with redundant synonym list ('validator / Luhn check / verification / detector') and an irrelevant pricing note. Could be trimmed to single sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-param tool with no output schema, description covers purpose, return values, and boundary (no payment). Lacks only minor details like exact return format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear parameter description. Tool description repeats the parameter but adds no new semantics beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool validates credit card numbers using Luhn algorithm and identifies card brand. It distinguishes itself from sibling validation tools (email, IP, phone, URL) by specific resource and verb.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'No payment processing, validation only', setting clear boundary. Among siblings, it's obvious for credit card validation, but no explicit when-not-to-use or alternatives mentioned.

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

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