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Test Card Generator

TestCardGenerator
Read-only

Test Card Generator: Test Card Generator creates card numbers that pass format and checksum validation, for testing checkout forms and payment UIs across major networks. They aren't real cards: no bank issued them, and they can't be charged or used to buy anything. Specify a brand to receive card numbers, security codes, expiration dates, issuers, and masked strings. (Cost: 1 credit)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "TestCardGenerator"
  }
}

Input Schema

NameRequiredDescriptionDefault
brandNoThe brand of the card to generatevisa
countNoThe number of test card numbers to generate
gatewayNoReturn this payment gateway's documented test cards instead of generated numbers. They trigger a known outcome in the gateway's test mode
scenarioNoWith gateway: the outcome to test, such as success, declined, insufficient_funds, expired_card, incorrect_cvc, fraud or 3ds_required (Stripe). Decline scenarios are mostly Visa cards, so the brand is ignored when the gateway has none for itsuccess
includeAvatarNoInclude an AI-generated face avatar for the card owner

Output Schema

NameRequiredDescriptionDefault
dataNo
errorNoError message, null on success
statusNo"ok" on success

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnly/openWorld annotations, it discloses that the cards are not real, are unchargeable, and cannot be used to buy anything — essential behavioral context for a generation tool an agent might otherwise treat as sensitive. It also states the credit cost and enumerates the returned artifacts (numbers, security codes, expiration dates, issuers, masked strings), which the annotations do not cover.

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

Conciseness4/5

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

The content is dense and front-loaded, leading with what is generated and following with the safety disclaimer and output payload. The only waste is the redundant 'Test Card Generator: Test Card Generator creates...' opener that restates the name and title.

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?

With an output schema present and annotations covering the safety profile, the description carries the remaining burden well: the fake-card disclaimer and the credit cost are the two things an agent most needs and neither is in structured data. Minor gaps remain around maximum count or rate/credit exhaustion behavior, but nothing critical 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 coverage is 100%, so the baseline is 3 and the schema already documents brand, count, gateway, scenario, and includeAvatar thoroughly. The description adds only that supplying a brand yields the full card payload; it does not explain count limits or the gateway/scenario interaction beyond what the schema fields already say.

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

Purpose4/5

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

The description states a concrete verb and resource — 'creates card numbers that pass format and checksum validation' — and scopes it to testing checkout forms and payment UIs. That distinguishes it in spirit from siblings like CardValidator or BINLookup, but no sibling is named explicitly, so the routing signal relies on the agent's inference.

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?

It gives a clear use context ('for testing checkout forms and payment UIs across major networks') and says 'Specify a brand to receive...' which tells the agent how to invoke it. There is no explicit when-not-to-use statement or named alternative (e.g., CardValidator for checking an existing number, RandomIdentityGenerator for fuller fake identities).

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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