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AiAgentKarl

fraud-prevention-mcp-server

tool_check_email_risk

Assess email fraud risk by detecting disposable addresses, spam traps, and deliverability issues, providing a fraud score and validity check.

Instructions

Check an email address for fraud risk, disposable services and spam traps.

Returns fraud score, validity, disposable flag, spam trap detection, and deliverability. Requires IPQS_API_KEY env var (free at ipqualityscore.com).

Args: email: Email address to validate and check strictness: Detection strictness 0-3, default 1

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYes
strictnessNo
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the return values (fraud score, validity, etc.) and the requirement of an API key, but lacks details on side effects, rate limits, or error handling.

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?

The description is concise with three sentences plus an argument list. It front-loads the purpose and efficiently includes return values and a requirement. No superfluous content.

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?

Given two parameters and no output schema, the description covers the inputs, outputs, and a key requirement. It is nearly complete, but missing details on error conditions or output format could be improved.

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

Parameters4/5

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

Schema description coverage is 0%, but the description adds meaning for both parameters: email is for validation, strictness has a range and default. This compensates well for the lack of schema descriptions.

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 'Check an email address for fraud risk, disposable services and spam traps', providing a specific verb and resource, and it distinguishes itself from sibling tools like tool_check_ip_reputation and tool_check_phone_risk.

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 implies usage by stating 'Check an email address', but it does not explicitly provide when to use versus alternatives or when not to use. No guidance on prerequisites beyond the API key.

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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