ENTIA Entity Verification

Run Risk Audit

run_risk_audit

Read-onlyIdempotent

PAID (requires SIGNAL plan or higher, from €29/month). Use when the user asks about the AI-readiness, SEO/LLM visibility or digital risk of a company's website domain. Run comprehensive AI-readiness + digital risk audit on any domain. Analyzes SSL, DNS, structured data, LLM visibility. Returns risk score 0-100. 5 req/min, 30s timeout.

Input Schema

Name	Required	Description
`name`	No	Optional business name for context
`domain`	Yes	Domain to audit (clinicadental.es, example.com)
`sector_id`	No	Optional sector hint (dental, legal, talleres, …)

Output Schema

Name	Required	Description	Default
`_meta`	No
`audit`	No
`domain`	No
`job_id`	No
`status`	No
`risk_level`	No
`risk_score`	No
`audit_token`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 14, 2026

changedInput schema / properties / domain / pattern

Previous value: -"^[a-z0-9]([a-z0-9.-]*[a-z0-9])?\\.[a-z]{2,}$"New value: +"^(?:https?://)?[A-Za-z0-9]([A-Za-z0-9.-]*[A-Za-z0-9])?\\.[A-Za-z]{2,}(?:[/?#].*)?$"

Changed1 schema field changedAug 18, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "description": "AI-readiness and digital risk audit of a domain.",
+  "properties": {
+    "_meta": {
+      "type": "object"
+    },
+    "audit": {
+      "type": "object"
+    },
+    "audit_token": {
+      "type": "string"
+    },
+    "domain": {
+      "type": "string"
+    },
+    "job_id": {
+      "type": "string"
+    },
+    "risk_level": {
+      "type": "string"
+    },
+    "risk_score": {
+      "type": "number"
+    },
+    "status": {
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

Changed4 schema fields changedMay 26, 2026

removedInput schema / $schema

Removed value: -"http://json-schema.org/draft-07/schema#"

removedInput schema / additionalProperties
```
Removed value: -false
```

changedInput schema / properties / domain / description

Previous value: -"Domain to audit (e.g. \"clinicadental.es\", \"example.com\")"New value: +"Domain to audit (clinicadental.es, example.com)"

changedInput schema / properties / sector_id / description

Previous value: -"Optional sector hint for more accurate scoring. Examples: dental, legal, talleres, estetica, inmobiliarias"New value: +"Optional sector hint (dental, legal, talleres, …)"

First observedMay 12, 2026

TDQS

A4.5/5.0

Behavior5/5

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

The description adds meaningful operational context beyond annotations: it is a paid tool requiring a SIGNAL plan or higher, has a rate limit of 5 requests per minute, and enforces a 30-second timeout. It also discloses the audit scope and that it returns a 0-100 risk score, which helps the agent understand cost and runtime constraints before invoking it.

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 short and front-loaded: the paid-plan constraint and primary usage trigger appear first, followed by scope, output, and rate-limit details. Every sentence carries useful information without 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 complexity and paid status, the description covers the essential points an agent needs: when to use it, plan requirement, scope of analysis, return value, rate limit, and timeout. Since an output schema exists, the description need not explain the full response structure.

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 description coverage is 100%, so the input schema already documents all three parameters thoroughly, including domain format and optional context fields. The description only refers to auditing 'any domain' and does not add parameter-specific meaning beyond the schema. Baseline 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 names a specific verb and resource: run a comprehensive AI-readiness and digital risk audit on a domain. It also lists the concrete analysis areas (SSL, DNS, structured data, LLM visibility) and the output (risk score 0-100), making the tool clearly distinguishable from lookup and search siblings.

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?

It gives clear trigger conditions: use when the user asks about AI-readiness, SEO/LLM visibility, or digital risk for a company's website domain. It also states the paid plan requirement. It does not explicitly name alternatives or when not to use it, but no sibling tool appears to provide an equivalent audit.

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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