Dechonet-MCP

Brand Impersonation Exposure

impersonation_exposure

Read-onlyIdempotent

Assess how exposed a domain is to brand impersonation and phishing, PASSIVELY: live typosquat/lookalike domains (homoglyph, omission, transposition, TLD swap) that actually resolve, operational subdomains (dev/staging/admin) exposed in CT logs, and whether a wildcard certificate exists — returning an A+ (low exposure) to F (high exposure) grade. Framing: a registered lookalike domain is not proof of impersonation — it may be a legitimate third party or the owner's own — so report it as exposure to verify, not as an accusation against that domain. Fully passive: public DNS delegation checks plus public CT-log queries, sending nothing to the target or the lookalike domains, so it is safe and lawful to run. Use lookalike_domains or subdomain_discovery for the raw per-tool detail. Read-only; requires no API key; rate-limited. Returns a text report: grade, counts, per-category findings, and a shareable report link.

Input Schema

Name	Required	Description	Default
`domain`	Yes	Registrable domain to assess for impersonation exposure (e.g., 'example.com'). Scheme and path are stripped.

Output Schema

Name	Required	Description
`grade`	Yes	Exposure grade A+ (low exposure) to F (high exposure)
`score`	Yes	0-100, higher = less exposed
`receipts`	No	Signed observation receipts behind this result, one per lookup: when, from where and under which rules version DechoNet observed it. Each url shows the record and checks its Ed25519 signature.
`wildcard`	No	Whether a wildcard certificate exists
`reportUrl`	Yes	Human-facing interactive report on dechonet.com
`typosquatCount`	Yes	Live third-party lookalike/typosquat domains (variants on the domain's own nameservers/IP are excluded)
`riskySubdomainCount`	Yes	Exposed operational subdomains found

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 15, 2026

addedOutput schema / properties / receipts

Added value: +{
+  "description": "Signed observation receipts behind this result, one per lookup: when, from where and under which rules version DechoNet observed it. Each url shows the record and checks its Ed25519 signature.",
+  "items": {
+    "properties": {
+      "id": {
+        "type": "string"
+      },
+      "tool": {
+        "type": "string"
+      },
+      "url": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "tool",
+      "id",
+      "url"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}

Changed1 schema field changedSep 16, 2026

changedOutput schema / properties / typosquatCount / description

Previous value: -"Live lookalike/typosquat domains found"New value: +"Live third-party lookalike/typosquat domains (variants on the domain's own nameservers/IP are excluded)"

AddedSep 8, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive), and the description adds substantial context beyond them: fully passive execution that sends nothing to the target or lookalike domains, no API key required, rate-limited, and the return format. This is exactly the extra behavioral layer annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is long, but front-loaded with the core purpose and grade output before the framing and passivity caveats, and each clause carries distinct information. Mildly dense in the middle, but no sentence is pure padding.

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?

An output schema exists, yet the description still briefly characterizes the return (grade, counts, per-category findings, shareable link), and it covers passivity, rate limits, and interpretation caveats. Nothing an agent needs to call it correctly is missing.

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 100% on the single parameter, and the schema already documents the domain example and the scheme/path-stripping behavior, so the description adds little parameter-level meaning. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb+resource ('Assess how exposed a domain is to brand impersonation and phishing') and enumerates the concrete signals it evaluates (typosquats, lookalikes, exposed subdomains, wildcard certs), plus the output form (A+ to F grade). It explicitly names the sibling tools lookalike_domains and subdomain_discovery as the raw-detail alternatives, so the agent can distinguish it without opening any schema.

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?

It tells the agent when this tool is the right choice (aggregate exposure grading) versus when to reach for the sibling tools ('Use lookalike_domains or subdomain_discovery for the raw per-tool detail'). It also frames how to interpret results — report as exposure to verify, not an accusation — which is genuine usage guidance rather than a restatement.

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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