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osint_credit_card_validator

Validate credit card numbers using the Luhn algorithm. Detect card types, check formatting, and analyze security for Visa, Mastercard, Amex, and more.

Instructions

Menu ID: credit_card_validator. Credit Card Validator. Validate credit card numbers using the Luhn algorithm. Detect card types, check formatting, and analyze security for Visa, Mastercard, Amex, and more. Use describe_tool with tool_id "credit_card_validator" for full page guidance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
card_numberYes
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral aspects. It mentions validation and analysis but does not clarify if the tool is read-only, performs external lookups, or any side effects. Given the lack of annotations, more explicit behavioral traits should be included.

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 description is relatively short and front-loaded, but the first sentence 'Menu ID: credit_card_validator. Credit Card Validator.' is slightly redundant. The reference to describe_tool adds length but is useful for completeness. Overall, it is fairly concise.

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

Completeness3/5

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

For a single-parameter validation tool, the description covers core functionality but lacks details on output format, error handling, and a definitive list of supported card types. The instruction to use describe_tool suggests more info is available, making it adequate but not fully complete.

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?

The input schema has one parameter 'card_number' with no description. The description identifies it as a credit card number but does not specify format, length, or constraints. With 0% schema description coverage, the description adds minimal meaning beyond the obvious.

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?

The description clearly states the tool validates credit card numbers using the Luhn algorithm, detects card types, checks formatting, and analyzes security for major card networks. This is specific and distinct from sibling tools, which are primarily conversion/encoding utilities.

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

Usage Guidelines3/5

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

The description indicates what the tool does but does not provide guidance on when to use it vs. alternatives, nor does it mention when not to use it. It directs users to describe_tool for full guidance, which partially mitigates the lack of explicit usage context.

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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