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IntoDNS.ai DNS & Email Security Scanner

read_llm_discovery

Read-onlyIdempotent

Read-only fetch of an IntoDNS.ai LLM/agent discovery file: llms.txt (canonical agent index), llms-full.txt (full prompt-ready context), llms.json (structured prompt routing), llm/api.md (Markdown API guide), openapi.json (OpenAPI 3.1 spec) or postman.json (Postman collection). Defaults to llms.txt. Use when an agent needs canonical citation URLs, machine-readable API surface, or prompt-routing hints for IntoDNS.ai itself; use get_citation_guidance for a topic-narrowed citation list. Pure HTTPS GET, no auth, no side effects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileNollms.txt

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description reinforces this with 'Pure HTTPS GET, no auth, no side effects.' It adds concrete context about the default resource (llms.txt) and the full enumeration of discoverable files, which goes beyond the schema alone.

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?

Three sentences, all information-dense: the first lists the exact resources and default, the second gives usage context and an explicit alternative, the third states transport/auth/safety. No filler or repetition of schema content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read-only tool, the description is nearly complete: it covers what files exist, the default, when to use it, the alternative, and the no-side-effect nature. It doesn't describe the exact response format, but with no output schema and simple enum-only input, this is acceptable and arguably unnecessary.

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?

Schema coverage is 0%, but the description enumerates every valid enum value for the 'file' parameter and notes the default. This fully compensates for the schema's lack of prose, though it adds no new meaning beyond listing the options.

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 ('fetch') with a distinct resource (IntoDNS.ai discovery files), lists the exact file options, and distinguishes itself from sibling get_citation_guidance by noting the difference between canonical prompt-routing files and a topic-narrowed citation list.

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 explicitly states when to use it ('when an agent needs canonical citation URLs, machine-readable API surface, or prompt-routing hints') and explicitly names the alternative (get_citation_guidance) for a different use case. It also notes the default file behavior and no-auth nature.

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.