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Lookalike Domain Check

lookalike_domains
Read-onlyIdempotent

Generate the typosquat/lookalike variants of a domain that phishers actually register — homoglyph swaps (l→1, o→0, rn→m), TLD swaps (.com→.co), character omissions, transpositions, repetitions, hyphenations — and check which of them are currently registered (live NS delegation via DoH). Use this to assess brand-impersonation and phishing exposure for a domain the user is responsible for. A registered variant is NOT proof of abuse (it may be an unrelated legitimate site) — follow up with whois_lookup on each hit for its owner and registration date. Read-only; requires no API key; rate-limited. Returns generated/checked counts and the registered variants with the technique that produced each.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to protect (e.g., 'example.com'), without scheme or path. Variants of its label and TLD are generated and checked.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kpisNoKey metrics as label/value pairs
gradeNoLetter grade (A+ to F) when the tool grades the target
scoreNo0-100 score when the tool scores the target
issuesNoDetected problems, severity-rated
statusYesOverall verdict, e.g. 'good' | 'warning' | 'bad' | 'info' | 'unknown'
actionsNoRecommended next actions, most important first
summaryNoOne-paragraph interpretation of the result
reportUrlYesHuman-facing interactive report for this exact lookup on dechonet.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark the tool as readOnly, openWorld, idempotent, and non-destructive, and the description adds real behavioral context: rate-limiting, no API key required, live NS delegation via DoH, and the important caveat that a registered variant is not proof of abuse. This goes well beyond the structured annotations.

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 dense but every clause carries critical information: technique enumeration, the live-check method, intended use case, a caveat, follow-up instruction, constraints, and return summary. The core action is front-loaded, and no filler is present.

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 single parameter, high schema coverage, rich annotations, and an output schema, the description fully covers what the tool does, how to interpret results, and what to do next. Nothing an agent needs to invoke it correctly is missing.

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

Parameters4/5

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

Schema coverage is 100% and the parameter description already explains format and constraints. The tool description adds useful meaning by specifying that variants of both the label and TLD are generated, clarifying what the single 'domain' parameter actually drives.

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 a specific verb ('Generate') and resource ('domain'), listing concrete variant types (homoglyph swaps, TLD swaps, omissions, transpositions, repetitions, hyphenations) and the registration check. It uniquely distinguishes this tool from all listed siblings, which are generic DNS/network or WHOIS utilities.

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 says to use this for assessing brand-impersonation and phishing exposure, and gives a concrete follow-up step with whois_lookup. It lacks an explicit when-not-to-use statement or named alternatives among siblings, but the context is clear and actionable.

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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