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IntoDNS.ai DNS & Email Security Scanner

by ai.intodns

generate_dmarc

Read-onlyIdempotent

Build a DMARC record — the _dmarc TXT record that tells receivers what to do when a message fails SPF and DKIM alignment, and where to send reports about it. The risk here is not syntax but policy. p=none monitors without affecting delivery and is where every deployment starts; p=quarantine sends failures to spam; p=reject refuses them outright, which silently destroys legitimate mail from any sender that was missed and gives that sender no explanation. Always publish a rua address: without aggregate reports there is no way to see which senders fail before enforcing against them. Use percentage to apply an enforcing policy to only part of the mail while rolling out. Returns the record, the host to publish it on (_dmarc), and warnings covering the mistakes that actually break mail — enforcing without reporting, reject at full coverage, pct at p=none, and strict alignment breaking subdomain senders and ESPs. Nothing is looked up or stored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pctNoAlias for `percentage`, matching the DNS tag name.
ruaNoAggregate report address(es). mailto: is added automatically.
rufNoForensic report address(es). Contains message content and is honoured by very few receivers.
policyNop= — start at 'none' and only enforce once reports show all legitimate senders aligning. Defaults to none.
percentageNopct= — share of mail the policy applies to, for a gradual rollout. Has no effect at p=none. Also accepted as `pct`.
spfAlignmentNoaspf= — strict requires an exact domain match and breaks subdomain senders.
dkimAlignmentNoadkim= — strict requires an exact domain match and breaks many ESPs.
reportIntervalNori= — seconds between aggregate reports. Defaults to 86400 (daily).
subdomainPolicyNosp= — a different policy for subdomains. Omitted when it matches the main policy.

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, openWorldHint, etc.), the description reveals additional behaviors: it returns the record, host, and warnings about common mistakes, and explicitly states 'Nothing is looked up or stored'. This adds meaningful context not captured by annotations and aligns with them.

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 yet information-dense, with each sentence serving a purpose: it defines the tool, explains risks, provides best practices, and describes outputs. It is well-structured, front-loaded with the core purpose, and avoids 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?

For a tool with 9 parameters and no output schema, the description covers critical context: policy trade-offs, reporting requirements, and common pitfalls, while also describing return values. It is sufficiently complete for an agent to use the tool correctly and safely.

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

Parameters5/5

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

Despite 100% schema coverage, the description adds substantial semantic value by explaining the real-world implications of parameters like policy, percentage, and rua, which are not fully captured in the schema descriptions. It clarifies how to use these parameters to avoid breaking mail delivery.

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 begins with a specific verb ('Build') and resource ('DMARC record'), clearly stating what the tool does. It distinguishes itself from siblings like generate_spf and check_dmarc by focusing on DMARC record generation and policy guidance, making its purpose unambiguous.

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?

The description provides explicit guidance on when to use each policy (p=none, p=quarantine, p=reject) and explains the consequences, such as 'reject silently destroys legitimate mail'. It also advises always publishing rua and using percentage for gradual rollout, giving clear context for safe usage.

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.

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