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theYahia

@metarebalance/dadata-mcp

clean_email

Validate an email address: fix typos and classify as disposable, corporate, or personal.

Instructions

Validate an email address. Fixes typos, detects disposable/corporate/personal type. Paid: 0.20 RUB/req.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesEmail address to validate
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses pricing (Paid: 0.20 RUB/req.) but does not mention rate limits, auth requirements, or any potential side effects like data storage.

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 extremely concise—two short sentences. No redundant information; every sentence adds value (purpose and pricing).

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?

With no output schema, the description omits return value details. It covers the tool's actions (validation, typo fix, type detection) and cost, but lacks specification of output format or behavior on invalid input.

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 the single 'email' parameter. The description adds context about typo fixing and type detection but does not provide additional parameter-level details beyond the schema.

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 it validates email addresses, fixes typos, and detects types (disposable/corporate/personal). This verb+resource combination is specific and distinguishes from sibling tools like clean_phone or suggest_email.

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?

No explicit guidance on when to use this tool versus alternatives like suggest_email. The description implies usage for validation but lacks context on exclusions or prerequisites.

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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