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Glama

IntoDNS.ai DNS & Email Security Scanner

by ai.intodns

check_fcrdns

Read-onlyIdempotent

Read-only FCrDNS (Forward-Confirmed Reverse DNS) audit for every IP that backs the domain's MX records. For each IP: looks up PTR record, then resolves that PTR's hostname back to A/AAAA records to confirm the round-trip. Returns per-IP PTR value, forward-resolution result, match verdict, and warnings (missing PTR, mismatched forward, generic ISP reverse). Use for mail deliverability audits, SpamExperts-style cluster checks, and any 'why is our mail being rejected' debugging; pair with check_blacklist for reputation signals. No auth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain name only, e.g. example.com (no URL, path, or port)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false Kubernete. The description reinforces these with 'Read-only' and 'No auth.' It adds detail on the exact steps performed (PTR lookup, forward resolution) and output contents (PTR value, forward result, match verdict, warnings), which is valuable behavioral context beyond annotations. However, it doesn't mention any rate limits or error handling, but given the read-only nature, this is acceptable.

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 concise and front-loaded. It states the purpose, method, outputs, and use cases in three sentences without fluff. Every sentence adds value.

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 simplicity (1 param, no output schema, but description details return values) and the presence of robust annotations, the description is fully adequate. Even though there's no output schema, the description lists the return components, which is sufficient.

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 description doesn't add significant parameter semantics because the schema already fully describes the single 'domain' parameter (100% coverage). The description implies it's a domain name but the schema already says 'Domain name only, e.g. example.com'. So baseline 3 is appropriate.

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 ('audit') and clearly identifies the resource (every IP backing the domain's MX records) while explaining the FCrDNS verification process. It distinguishes itself from sibling tools like check_blacklist by specifying its unique focus on reverse DNS validation.

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 usage scenarios: 'mail deliverability audits, SpamExperts-style cluster checks, and any why is our mail being rejected debugging' and recommends pairing with check_blacklist for reputation signals. This gives clear guidance on when to use and complements alternatives.

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

A4.1/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose, and cross-references between tools (e.g., check_spf vs check_email_security vs check_sender_requirements) explicitly state when to use each one. Overlapping behaviors are carefully delineated (e.g., scan_domain vs get_everything_report vs start_deep_scan) with latency and depth tradeoffs explained. No two tools appear to do the same thing.

Naming Consistency4/5

Nearly all tool names follow a verb_noun snake_case pattern (check_*, generate_*, get_*, create_*, scan_*), with precise verbs matching each action. Minor deviations include 'nis2_quickscan' (no verb) and a few compound names like 'whois_lookup', but these are isolated. The variety of verbs is semantically justified by the broad domain, so the naming is predictable and readable.

Tool Count2/5

At 45 tools, this is far beyond the 16-25 'heavy' range and nearly double the 25 threshold. While the server covers a wide range of DNS, email, and web checks, a 45-tool surface is likely to overwhelm agents and increase selection errors. Many tools could be consolidated (e.g., individual check_* tools into one combined check) without sacrificing clarity.

Completeness5/5

The tool set meticulously covers the domain: DNS (SPF, DKIM, DMARC, DNSSEC, propagation, whois), email security (blacklist, FCrDNS, MTA-STS, SMTP TLS, TLSA, BIMI, raw email analysis, test sessions), web security (headers, CSP, HTTP/3), reporting (PDF, snapshots, badges), and compliance (NIS2, Internet.nl deep scans). There are no obvious gaps for the stated purpose of DNS & email security scanning; every check has a corresponding generator or explainer.

Resources