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email_check

Email validation for signup forms, lead lists and CRM cleanup: checks syntax, MX mail servers, disposable or temporary domains, role addresses (info@, sales@) and free providers. Returns a deliverable_guess. No SMTP probe, no data stored. Price $0.001 USDC per call via x402. Example output: {"email":"jane@acme.com","valid_syntax":true,"domain":"acme.com","mx_records":["10 mx1.acme.com."],"has_mail_server":true,"disposable":false,"role_account":false,"free_provider":false,"deliverable_guess":"likely"}

Input Schema

NameRequiredDescriptionDefault
emailYesEmail address to validate

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations present, the description carries the full behavioral burden and does so: it discloses the absence of an SMTP probe, that no data is stored, the exact per-call price and payment rail (x402, $0.001 USDC), and the deliverable_guess nature of the verdict. This is unusually complete side-effect and cost disclosure.

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 first sentence front-loads purpose and scope, with cost and caveats appended afterwards. The inline example output is long but earns its space since no output schema exists; the run-on first sentence is the only minor bloat.

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?

For a single-parameter tool with no output schema, the description supplies the return-field shape via an example, the pricing model, and the safety profile. The one gap is explicit routing guidance against email_check_full, which the sibling list makes a realistic confusion.

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, so the baseline is 3. The description adds context about what happens to the input (syntax, MX, domain classification) but nothing about input format or constraints beyond the schema's 'Email address to validate'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (validation) and resource (email addresses) and enumerates exactly which checks run: syntax, MX, disposable domains, role addresses, free providers. It only implicitly differentiates from the sibling email_check_full via 'No SMTP probe', rather than naming it as the heavier alternative.

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?

Gives concrete scenarios (signup forms, lead lists, CRM cleanup) plus an explicit exclusion ('No SMTP probe'), which tells the agent this is the lightweight path. It never names email_check_full or states the condition that should route an agent there.

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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