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Email address check

red_email_check

Scores one email address 0-100 with a verdict (ok, risky, disposable, undeliverable, invalid) and the evidence under it: every point lost is itemised with the field that proves it. 12,141 disposable domains from two maintained open lists pinned to a commit, 4,897 free providers, 1,018 role names, typo fix (gmial.com > gmail.com), live MX/SPF/DMARC. No SMTP probe, no API key. $0.005 per call, paid over x402 (USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesThe address to check, e.g. someone@example.com.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: it discloses the score range, the verdict enum, the itemised-evidence response shape, the data sources with counts, and critically the operational profile — no SMTP probe, no API key, $0.005 per call paid over x402 (USDC). Cost and payment-path disclosure is exactly the kind of behavioral context annotations would never provide.

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 leading sentence front-loads the action and output, and every following clause (data-source counts, method, pricing) earns its place. It is dense to the point of reading as one long run-on block, which slightly hurts scannability, but there is essentially no filler.

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?

No output schema exists, so the description must, and does, explain the return values (0-100 score, verdict enum, itemised evidence per lost point). Combined with the pricing and method disclosure, an agent has everything needed to call this correctly.

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 description coverage is 100% and the single 'email' parameter is documented with an example in the schema itself. The description adds no format or syntax detail beyond what the schema already supplies, so the baseline 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?

States a specific verb and resource ('Scores one email address 0-100') and enumerates the exact output verdicts (ok, risky, disposable, undeliverable, invalid) plus the evidence model. This clearly separates it from siblings like red_domain_check, red_dnsbl, red_whois and util_phone without the agent needing to open any schema.

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 use case (screening/validating a single address) but never states when to reach for this tool versus an alternative, nor any exclusions or prerequisites for calling it. It distinguishes its *method* ('No SMTP probe') but not its *usage conditions*, leaving this at implied guidance.

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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