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Kaidn-io

Kaidn-mcp

Official
by Kaidn-io

Check a phone number

check_phone

Validate a phone number and retrieve line type, carrier, and fraud score to assess risk.

Instructions

Validity, line type, carrier and fraud score for one phone number. Consumes one row of monthly quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
phoneYesThe phone number, E.164 or national
countryNoISO country code to parse a national number against, e.g. 'US'
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly mentions consuming one row of monthly quota, which is a key operational detail (rate limit/cost). It also lists the output data points. However, it does not mention any side effects, permissions, or error conditions, which for a simple lookup may be acceptable but leaves some gaps.

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 two sentences, front-loaded with the primary purpose, and includes a crucial quota warning without any unnecessary words. It is highly concise and well-structured.

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 the simplicity of the tool (two params, full schema coverage, no output schema), the description adequately covers its behavior and outputs. It lists the returned fields and the quota consumption, but it could be more complete with explicit usage context relative to sibling tools, though that is mostly a usage-guideline issue.

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% for both parameters, so the description does not need to add parameter meaning. It adds no extra semantics beyond the schema's existing descriptions for 'phone' and 'country', so the baseline score of 3 applies.

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's function: it returns validity, line type, carrier, and fraud score for a single phone number. This specific verb-less enumeration distinguishes it from sibling tools like check_email and check_ip, which target different entity types.

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 the tool is for phone number checks but does not explicitly discuss when to use it versus alternatives like check_email or check_ip. No exclusions or prerequisites are mentioned, so usage guidance is minimal but not misleading.

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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