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dns-doctor

by dev.dnsdoctor

check_record

Read-onlyIdempotent

Check whether a DNS change has landed: reads the record from the domain's OWN nameservers (cache-free) and from two public caching resolvers, and reports whether they agree. kind is one of spf|dmarc|txt|mx|cname|a|aaaa — pass the kind, not a query name: dmarc reads TXT at _dmarc. and spf reads apex TXT, each filtered to the matching record. host prepends a label (txt, cname, a and aaaa only). Empty values mean the record is genuinely absent. When in_sync is false, max_wait_seconds is the largest remaining cached TTL — the wait before those resolvers refresh. This samples two resolvers, so never describe it as worldwide or as propagation coverage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostNoOptional label to prepend to the domain (e.g. 'mail' to check mail.<domain>) — honored for txt, cname, a and aaaa only; spf, dmarc and mx derive their own query name.
kindYesWhich record to read; the right query is derived from it — 'dmarc' reads TXT at _dmarc.<domain> filtered to v=DMARC1, 'spf' reads the apex TXT filtered to v=spf1, so don't prefix the domain yourself.
domainYesThe domain to check, e.g. example.com. Bare registrable names and subdomains both work; scheme, path or port do not belong here. Unicode names are accepted and normalized to punycode.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior5/5

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

The description goes far beyond the readOnlyHint and idempotentHint annotations. It details the exact query logic for each kind (e.g., dmarc reads TXT at _dmarc.<domain>), explains that empty values mean genuinely absent, and clarifies the meaning of in_sync false and max_wait_seconds. The caveat about sampling only two resolvers is critical behavior context.

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 appropriately sized and front-loaded with the main purpose, then systematically covers kind semantics, host restrictions, output interpretation, and limitations. Every sentence earns its place, with no filler or redundancy.

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 tool's complexity (multiple record kinds, derived queries, cache-free vs caching resolvers), the description covers all essential aspects. The output schema exists, and the description still explains key output semantics like empty values and max_wait_seconds, making it thoroughly complete.

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 input schema already provides comprehensive descriptions for all three parameters (100% coverage), including kind's derived query logic and host's allowed types. The tool description largely restates this information, adding no significant new parameter semantics beyond the schema.

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 uses a specific verb 'Check' and states the exact resource: 'whether a DNS change has landed' by reading from the domain's own nameservers and two public resolvers. This clearly distinguishes it from sibling tools like check_dkim_selector or check_reverse_dns, which target specific record types.

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?

The description explicitly states when to use: 'Check whether a DNS change has landed' and provides an exclusion: 'never describe it as worldwide or as propagation coverage' because it samples only two resolvers. However, it does not name alternative sibling tools for specific DNS checks, so it lacks explicit alternative 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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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