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AiAgentKarl

fraud-prevention-mcp-server

tool_check_phone_risk

Assess phone number fraud risk by validating numbers and detecting VoIP, prepaid, and carrier indicators. Returns validity, line type, and fraud score.

Instructions

Validate a phone number and check for fraud risk, VoIP and prepaid indicators.

Returns validity, line type, carrier, VoIP flag, and fraud score. Requires IPQS_API_KEY env var (free at ipqualityscore.com).

Args: phone: Phone number in E.164 format (e.g. +14155552671) or local format country: ISO country code for local numbers (default: US)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
phoneYes
countryNoUS
Behavior4/5

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

No annotations are provided, so the description must carry the full burden. It discloses that an external API is called (via API key) and what the tool returns. It does not mention rate limits or error handling, but for a read-only validation tool this is adequate. The description is transparent about the external dependency.

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 very concise—6 sentences covering purpose, outputs, prerequisite, and parameters. It is front-loaded with the core action and structured logically. No unnecessary words.

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?

Given two parameters, no output schema, and no annotations, the description is complete. It explains the tool's purpose, what it returns, a required environment variable, and parameter formats. An agent has enough information to use the tool correctly.

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

Parameters5/5

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

With schema description coverage at 0%, the description fully explains the parameters: phone should be in E.164 or local format with example, and country defaults to US. This adds critical meaning beyond the schema's type-only definition.

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 a phone number and checks for fraud risk, VoIP, and prepaid indicators. It specifies the return fields, making the purpose unambiguous. The sibling tools (e.g., tool_check_email_risk, tool_check_ip_reputation) are for different data types, so this tool is well-distinguished.

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?

The description mentions a prerequisite (IPQS_API_KEY env var) and provides a registration link. While it does not explicitly state when to use this tool versus alternatives, the sibling tool names imply usage contexts. Some guidance on when not to use is missing, but the purpose is clear enough.

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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