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MLNops

by Milindu-Weerawarna
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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email_security_check

Check SPF, DKIM, and DMARC DNS records for a domain to evaluate email anti-spoofing configuration and identify misconfigurations that enable phishing.

Instructions

Check SPF, DKIM, and DMARC DNS records for a domain to assess basic email anti-spoofing configuration.

DKIM detection is best-effort here. It checks a fixed list of common selectors used by major email providers, since DKIM selectors cannot be discovered via DNS without already knowing them.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "domain": "<domain>"
    },
    "name": "email_security_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
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. It honestly discloses that DKIM detection is best-effort due to a fixed list of common selectors, explaining the limitation. This adds value beyond the schema. However, it could also note any potential issues with SPF and DMARC checks.

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: the first states the purpose clearly, and the second provides a key behavioral detail. It is front-loaded and contains no extraneous words.

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 presence of an output schema, the description does not need to detail return values. It covers purpose and a key limitation. Adding a brief note about what SPF, DKIM, and DMARC checks entail would improve completeness, but it is adequate for a simple tool.

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

Parameters2/5

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

Schema coverage is 0%, so the description should compensate. It mentions 'domain' in context but does not explain the parameter's format, requirements, or examples. The only added meaning is that the domain is the target for the security check.

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 checks SPF, DKIM, and DMARC DNS records for a domain, with the specific purpose of assessing basic email anti-spoofing configuration. This is a specific verb-resource combination that distinguishes it from sibling tools like dns_enumeration or whois_lookup.

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 usage for email security checks but does not explicitly state when to use this tool versus alternatives, nor does it mention when not to use it. It provides no exclusions or comparisons to siblings like dns_enumeration.

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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