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Generate a synthetic payment card fixture

generate-card-number
Read-onlyIdempotent

Generate a synthetic payment-card fixture. Use for payment-form UI tests requiring a Luhn-valid card number. Returns {number, brand, expiry, cvc}; values are synthetic, not issued credentials.

Input Schema

NameRequiredDescriptionDefault
seedNoOptional deterministic seed for reproducible fake card fixtures.
brandNoSynthetic card brand: visa, mastercard, amex or discover.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / brand / description
      Added value: +"Synthetic card brand: visa, mastercard, amex or discover."
    • addedInput schema / properties / seed / description
      Added value: +"Optional deterministic seed for reproducible fake card fixtures."
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so safety is largely covered. The description adds value beyond them by disclosing the return shape ({number, brand, expiry, cvc}) and the important caveat that values are synthetic and not issued credentials, which an agent must not treat as real payment data.

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

Conciseness5/5

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

Three short sentences, front-loaded with purpose, then usage, then return/safety caveat. Every sentence carries distinct information with no redundancy.

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

Completeness5/5

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

With no output schema, the description steps in to describe the returned object and its synthetic nature, and the annotations cover the safety profile. Nothing essential for correct invocation is missing.

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 description coverage is 100% and both parameters (seed, brand) are fully documented in-schema, including the enum values and the determinism meaning of seed. The description adds nothing about parameters, so the baseline 3 is appropriate.

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?

States a specific verb and resource ('Generate a synthetic payment-card fixture') and immediately narrows scope to Luhn-valid card numbers for payment-form UI tests. Despite a large sibling set of generate-* tools, the resource noun (payment-card) makes the distinction unambiguous without naming an alternative.

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?

Gives a clear use case ('payment-form UI tests requiring a Luhn-valid card number') and implicitly warns that this is for fixtures, not real credentials. It stops short of naming when-not-to-use or pointing to a sibling (e.g., generate-ssn or generate-token), so no exclusion guidance is present.

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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