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email_check_full

One call email risk check: everything in email_check plus sender domain health (domain age, registrar, SPF, DMARC, website reachable) and a 0-100 risk score with accept/review/reject verdict. Use for fraud screening, lead qualification and signup gating. Price $0.004 USDC per call via x402. Example output: {"email":"jane@acme.com","has_mail_server":true,"disposable":false,"domain_health":{"registrar":"GoDaddy.com, LLC","age_days":4021,"spf":"v=spf1 include:_spf.google.com ~all","dmarc":"v=DMARC1; p=reject","website_reachable":true},"risk_score":0,"risk_reasons":[],"verdict":"accept"}

Input Schema

NameRequiredDescriptionDefault
emailYesEmail address

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does substantial work: it discloses the payment/auth requirement and unit cost ('$0.004 USDC per call via x402'), the verdict taxonomy (accept/review/reject), and the risk-score range. Gaps remain around failure modes, invalid-email handling, and latency/rate limits, which matters for a paid call.

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?

Front-loaded with the differentiator and scope, then use cases, then price, then a concrete return example — no filler sentences. The example JSON is long but earns its place because there is no output schema.

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?

No annotations and no output schema, so the description must cover behavior and returns; it does so via the risk-score/verdict explanation and a full example response. It stops short of error behavior, timeouts, and what happens on malformed input, which an agent about to spend $0.004 per call would want.

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

Parameters4/5

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

Only one parameter and schema coverage is 100%, so the schema already documents 'email'. The description adds no format or validation detail for the address (e.g., whether role addresses or unicode domains are acceptable), so it does not exceed the baseline for a single fully-documented param.

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 ('email risk check') and explicitly scopes it as a superset of the sibling: 'everything in email_check plus sender domain health... and a 0-100 risk score'. The included signals (domain age, registrar, SPF, DMARC, website reachability) and outputs (risk score, verdict) let an agent distinguish it from email_check without opening the schema.

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?

Names concrete use cases: 'fraud screening, lead qualification and signup gating', which tells the agent the decision context this tool serves. It implies when to prefer email_check (basic check) by framing this as the fuller version, but never states an explicit exclusion or cost-sensitive trade-off rule.

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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