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Glama

dns-doctor

by dev.dnsdoctor

validate_dmarc_record

Read-onlyIdempotent

Validate a pasted DMARC record: parsed tags, level'd findings, and whether it is valid. No DNS lookup — pass the record string itself. upgrade_record previews a stronger policy and is capped at p=quarantine: a pasted record carries no alignment evidence, and p=reject is unlocked only by aggregate-report evidence over a full reporting window (monitoring), never by a scan. Present any returned record verbatim.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recordYesThe DMARC record text to validate, e.g. 'v=DMARC1; p=none; rua=mailto:reports@example.com'. The record value only — not the _dmarc hostname it is published at.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / record / description
      Added value: +"The DMARC record text to validate, e.g. 'v=DMARC1; p=none; rua=mailto:reports@example.com'. The record value only — not the _dmarc hostname it is published at."
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly and idempotent, but the description adds significant behavioral specifics: no DNS lookup, the policy unlock logic, and the instruction to present returned records verbatim. No contradiction with annotations.

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 description is moderately sized, with focused sentences that convey purpose, constraints, and alternatives without unnecessary filler. Slightly dense but efficient.

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?

Given the output schema exists, the description covers all essential aspects: what it validates, how to pass the input, policy limitations, and references to related tools. An agent would have enough context to invoke it 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?

The schema provides 100% coverage of the 'record' parameter with a clear example and clarification about the hostname. The description reinforces these points but adds no new parameter-level semantics beyond what the schema already offers.

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 clear verb ('validate') and resource ('DMARC record') with explicit outputs (parsed tags, level'd findings, validity). Distinguishes from siblings by specifying it handles a pasted record string, not a DNS lookup.

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

Usage Guidelines5/5

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

Explicitly states 'No DNS lookup — pass the record string itself' and clarifies when p=reject is unlocked, referencing upgrade_record as an alternative. This provides clear context on when to use this tool versus others.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct DNS or email authentication task. Despite multiple DMARC-related tools, their purposes are clearly differentiated: build_dmarc_upgrade upgrades policies, generate_dmarc_record creates new ones, validate_dmarc_record validates pasted records, and scan_domain vs get_report differentiate fresh vs cached scans.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., build_dmarc_upgrade, check_record, scan_domain). No mixing of naming conventions, making the set predictable and easy to navigate.

Tool Count5/5

With 11 tools, the server is well-scoped for a DNS/email authentication diagnostics tool. The number covers essential operations without being overwhelming or sparse.

Completeness4/5

The tool set covers core workflows: DMARC management (generate, validate, upgrade, parse reports), DNS checks (propagation, reverse DNS, SPF lookups), and DKIM selector checks. Minor gaps exist, such as the absence of SPF validation or DKIM signature verification, but the main diagnostic and monitoring use cases are supported.

Resources