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DMARC check

dmarc_check
Read-onlyIdempotent

Reads and validates a domain's DMARC record: policy, reporting addresses, alignment and percentage.

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": "dmarc_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYesA domain name such as example.com. A full URL or an email address is reduced to its domain.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description usefully indicates that this is a live lookup and validation rather than a cached read, and lists the record components it inspects, but it says nothing about what happens when no DMARC record exists or the domain fails to resolve. That behavior, which matters for a validation tool, is left undocumented.

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?

It is a single front-loaded sentence with no filler, and the resource is named first. The trailing list of inspected fields is dense but useful, so nothing needs to be cut.

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 one-parameter, read-only lookup with full annotation coverage and no output schema, the description is nearly sufficient: it states the purpose, the normalization behavior comes from the schema, and the inspected fields hint at what is returned. Only the failure or no-record case is missing, which is a minor gap at this complexity.

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?

The schema documents its single 'domain' parameter at 100% coverage, including normalization behavior (URLs and emails are reduced to their domain). The description adds no parameter meaning beyond that, so the baseline 3 applies.

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?

The description names a specific verb ('Reads and validates') and a specific resource ('a domain's DMARC record'), and it enumerates the record fields examined (policy, reporting addresses, alignment, percentage). That makes the tool clearly distinguishable from DNS-family siblings such as spf_check or dkim_check, although it never says so explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use or when-not-to-use guidance, no mention of prerequisites (the domain must exist and be resolvable), and no pointer to alternatives such as spf_check or dkim_check for related email-authentication checks. Usage is only implied by the tool's subject matter.

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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