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IntoDNS.ai DNS & Email Security Scanner

by ai.intodns

create_email_test

Create a new IntoDNS.ai inbound email-test session. Returns a unique single-use test email address (valid 60 minutes) and a testId used by get_email_test or poll_email_test. This is an additive, non-idempotent POST: every call creates a fresh session but never modifies prior sessions. language controls result text (en/nl/de/fr, default en). Use to debug an outbound message's SPF/DKIM/DMARC, headers, and spam triggers; after sending, call poll_email_test. No auth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoResult languageen

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses behavioral traits beyond annotations: it specifies the tool is a non-idempotent POST, creates a fresh session each time without modifying prior sessions, returns a single-use email valid for 60 minutes, and requires no auth. This adds valuable context that annotations only hint at.

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 well-structured, covering purpose, return value, behavior, parameter, usage scenario, and auth requirement in four sentences. Every sentence contributes essential information with no fluff or repetition.

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 role as a creation step in a workflow, the description is complete: it explains what it returns (test email and testId), the expiry, the language option, and exactly how to follow up (poll_email_test). With no output schema, the description fulfills the need to describe the return value adequately.

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 description coverage is 100% (the only param 'language' is described as 'Result language' with an enum and default). The description adds 'language controls result text (en/nl/de/fr, default en)', which is essentially a restatement of the schema info. It doesn't provide significant new meaning beyond what the schema already offers, so the baseline of 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 clearly states what the tool does: it creates a new inbound email-test session. It specifies the verb 'create' and the resource 'inbound email-test session', and distinguishes itself from siblings by explaining the returned testId is used by get_email_test or poll_email_test. This makes it 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 gives explicit guidance on when to use the tool: 'Use to debug an outbound message's SPF/DKIM/DMARC, headers, and spam triggers; after sending, call poll_email_test.' It also indicates the workflow and implicitly suggests not to use it for other tasks, providing clear context and next steps.

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