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bitdefender.nl

Scan history Scanned 2026-05-18 10:56 UTC
Changes since selected scan Not comparable because methodology information is unavailable

Result summary

Measured coverage

58/100

Methodology grade

C

Methodology legacy

47 checkpoints assessed

Find
4/8 passed
Read
18/25 passed
Act
2/14 passed
Readiness profiles Filter the detailed results by purpose

Select a profile to filter the detailed results.

Action plan

Priority actions Prioritized by exact impact on the overall stable-core score.
Failed High-value schema types +5 overall pts

No high-value schema types found. We check for 17 recognized types including Article, Product, SoftwareApplication, FAQPage, LocalBusiness, VideoObject, and more.

High-value schema types
HIGH

Certain schema types (Article, Product, FAQPage, etc.) trigger rich results in Google and are used by AI search engines like Perplexity and ChatGPT to generate citations and structured answers.

Add JSON-LD markup for content-appropriate types like Article, Product, SoftwareApplication, FAQPage, LocalBusiness, Service, Event, or VideoObject to improve visibility in AI-powered search results.

JSON-LD html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Your App Name",
  "operatingSystem": "Web",
  "applicationCategory": "BusinessApplication",
  "offers": {
    "@type": "Offer",
    "price": "0",
    "priceCurrency": "USD"
  }
}
</script>
Failed WebMCP Declarative API +4 overall pts

No WebMCP signals found.

WebMCP Declarative API
HIGH

WebMCP is the W3C proposal for exposing website functionality directly to AI agents. Declarative tool annotations on forms let agents perform actions (search, purchase, book) without screen scraping.

Implement WebMCP to let AI agents interact with your site. Declarative: add tool-name and tool-description attributes to <form> elements. Imperative: use navigator.modelContext.provideContext() to register tools.

<form tool-name="search" tool-description="Search products by keyword">
  <input type="text" name="query" tool-param-description="Search query">
  <button type="submit">Search</button>
</form>
Failed A2A Agent Card +4 overall pts

No A2A Agent Card found at /.well-known/agent-card.json or /.well-known/agent.json.

A2A Agent Card
HIGH

Google's Agent-to-Agent (A2A) protocol enables autonomous agent-to-agent communication. An Agent Card at /.well-known/agent-card.json (new) or /.well-known/agent.json (legacy) advertises your agent's capabilities to other AI systems.

Create an A2A Agent Card at /.well-known/agent-card.json with required fields: name, description, url, version, capabilities, supportedInterfaces.

.well-known/agent.json json
{
  "name": "My Agent",
  "description": "An AI assistant for customer support",
  "url": "https://bitdefender.nl/agent",
  "version": "1.0.0",
  "capabilities": {
    "streaming": true,
    "pushNotifications": false
  },
  "supportedInterfaces": [
    {
      "url": "https://bitdefender.nl/mcp",
      "transport": "http",
      "protocol": "MCP/2025-06-18",
      "protocolBinding": "MCP",
      "protocolVersion": "2025-06-18"
    }
  ],
  "preferredTransport": "MCP",
  "skills": [
    {"id": "support", "name": "Customer Support"}
  ]
}
Failed OpenAPI / API documentation +3 overall pts

No OpenAPI or Swagger documentation found.

OpenAPI / API documentation
HIGH

OpenAPI specifications let AI agents understand and call your API programmatically. AI coding assistants and agent frameworks use OpenAPI to generate correct API calls automatically.

Create an OpenAPI 3.x specification and serve it at /openapi.json or /.well-known/openapi to enable AI agents to discover and use your API.

openapi.json json
{
  "openapi": "3.1.0",
  "info": {
    "title": "My API",
    "version": "1.0.0"
  },
  "paths": {
    "/api/search": {
      "get": {
        "summary": "Search items",
        "parameters": [
          {"name": "q", "in": "query", "schema": {"type": "string"}}
        ]
      }
    }
  }
}
Failed Content Signals (robots.txt) +3 overall pts

No Content-Signal directive found in robots.txt. AI crawlers cannot read your usage preferences.

Content Signals (robots.txt)
HIGH

Content Signals is a draft IETF standard (draft-romm-aipref-contentsignals) for declaring AI content usage preferences in robots.txt. Compliant crawlers respect signals like `ai-train=no` (do not train on this content) or `search=yes` (use for search). It is part of Cloudflare's agent web stack and gates Level 2 on their readiness scanner.

Add a `Content-Signal:` line to robots.txt declaring your AI training, search, and ai-input preferences.

robots.txt plain
# Add to /robots.txt:
Content-Signal: ai-train=yes, search=yes, ai-input=yes
Failed Content freshness signals +3 overall pts

No content freshness signals found. AI systems cannot determine when this content was last updated.

Content freshness signals
HIGH

AI systems strongly prefer recent content. ChatGPT gives 3.2× more citations to content updated within 30 days. Clear date signals (dateModified, article:modified_time) help AI determine your content's recency.

Add content date signals so AI systems can assess freshness. Use dateModified in JSON-LD, <meta property="article:modified_time">, or at minimum ensure your server sends a Last-Modified header. Content updated within 3 months averages 67% more AI citations.

JSON-LD html
<!-- Option 1: JSON-LD (preferred) -->
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Your Article Title",
  "datePublished": "2026-01-15T09:00:00Z",
  "dateModified": "2026-02-28T14:30:00Z"
}
</script>

<!-- Option 2: Open Graph meta tags -->
<meta property="article:published_time" content="2026-01-15T09:00:00Z">
<meta property="article:modified_time" content="2026-02-28T14:30:00Z">

<!-- Option 3: HTML time element -->
<time datetime="2026-02-28T14:30:00Z">Updated February 28, 2026</time>

<!-- Server-level: Ensure Last-Modified header is sent -->
# Nginx: add_header Last-Modified $date_gmt;
# Apache: FileETag MTime (default)
Failed Link response headers +3 overall pts

No Link response header found on the root page. Agents must parse HTML to discover related resources.

Link response headers
HIGH

Link response headers (RFC 8288) tell agents about machine-readable resources at request time. Cloudflare's isitagentready.com and other scanners explicitly look for `api-catalog`, `service-desc`, `service-doc`, and `sitemap` rels to enable agent discovery without parsing HTML.

Add an RFC 8288 Link response header advertising your OpenAPI document, API catalog, and sitemap so agents can discover them at request time.

Server config plain
# Nginx
add_header Link '</.well-known/api-catalog>; rel="api-catalog", </openapi.json>; rel="service-desc", </sitemap.xml>; rel="sitemap"' always;

# Phoenix / Plug
plug :put_link_headers

defp put_link_headers(conn, _opts) do
  put_resp_header(
    conn,
    "link",
    "</.well-known/api-catalog>; rel=\"api-catalog\", " <>
      "</openapi.json>; rel=\"service-desc\", " <>
      "</sitemap.xml>; rel=\"sitemap\""
  )
end

# Test: curl -I https://bitdefender.nl/ | grep -i '^link:'
Failed Entity linking (@id) +3 overall pts

No JSON-LD entities use @id for entity linking.

Entity linking (@id)
HIGH

Entity linking via @id creates a connected graph of your content. AI systems can follow these references to build deeper understanding of relationships between your pages, organization, and content.

Add @id properties to your JSON-LD entities (e.g. "@id": "bitdefender.nl/#organization") to enable cross-referencing between entities.

JSON-LD html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "Organization",
      "@id": "https://bitdefender.nl/#organization",
      "name": "Your Company",
      "url": "https://bitdefender.nl"
    },
    {
      "@type": "WebSite",
      "@id": "https://bitdefender.nl/#website",
      "name": "Your Site",
      "url": "https://bitdefender.nl",
      "publisher": { "@id": "https://bitdefender.nl/#organization" }
    }
  ]
}
</script>
Failed FAQPage schema +3 overall pts

No FAQPage schema found. Sites with FAQPage schema are 8× more likely to be cited by ChatGPT.

FAQPage schema
HIGH

FAQPage schema is one of the strongest structured data signals for AI citation. Research shows websites with FAQPage schema are 8× more likely to appear in ChatGPT search results compared to those without it.

Add FAQPage structured data with Question/Answer pairs covering common queries about your product or service. Pages with FAQPage schema are 8× more likely to be cited by ChatGPT, making this one of the highest-ROI structured data investments for AI visibility.

JSON-LD html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is AI agent readiness?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "AI agent readiness measures how well a website can be discovered, understood, and interacted with by AI systems."
      }
    },
    {
      "@type": "Question",
      "name": "How do I improve my AI readiness score?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add structured data, ensure clean semantic HTML, allow AI crawlers in robots.txt, and implement agent protocols."
      }
    }
  ]
}
</script>
Failed Author attribution +3 overall pts

No author attribution found. 96% of Google AI Overview citations come from sources with strong E-E-A-T signals including clear authorship.

Author attribution
HIGH

Author attribution is a key E-E-A-T signal. Google reports 96% of AI Overview citations come from sources with strong E-E-A-T, and expert-authored content is 3.2× more likely to be cited than generic staff-written content.

Add author information using JSON-LD (preferred), <meta name="author">, or <a rel="author">. Expert authorship is 3.2× more likely to earn AI citations.

JSON-LD html
<!-- Option 1: JSON-LD author in Article (preferred) -->
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Your Article Title",
  "author": {
    "@type": "Person",
    "name": "Jane Smith",
    "url": "https://bitdefender.nl/team/jane-smith"
  }
}
</script>

<!-- Option 2: Meta tag -->
<meta name="author" content="Jane Smith">

<!-- Option 3: Linked author -->
<a rel="author" href="https://bitdefender.nl/team/jane-smith">Jane Smith</a>
Partial Heading hierarchy +2 overall pts

Multiple <h1> tags found (2) and level skips detected. Use exactly one <h1> per page.

Heading hierarchy
MEDIUM

AI agents use headings to build a content outline and determine topic hierarchy. A clear h1→h2→h3 structure helps AI systems extract and summarize your content accurately.

Ensure exactly one <h1> per page. Use sequential heading levels without skipping (h1 -> h2 -> h3, not h1 -> h3). All headings should contain meaningful text. See developer.mozilla.org/en-US/docs/Web/HTML/Element/Heading_Elements for heading element documentation.

HTML html
<h1>Page Title - One Per Page</h1>
  <h2>Main Section</h2>
    <h3>Subsection</h3>
    <h3>Subsection</h3>
  <h2>Another Section</h2>
    <h3>Subsection</h3>
Failed OAuth Discovery +2 overall pts

No OAuth/OIDC discovery document found at /.well-known/oauth-authorization-server or /.well-known/openid-configuration.

OAuth Discovery
HIGH

OAuth/OIDC discovery (RFC 8414, OpenID Connect Discovery 1.0) lets agents authenticate with your APIs without out-of-band setup. Cloudflare's isitagentready.com requires this for Level 4-5 readiness.

Publish an OAuth 2.0 Authorization Server Metadata document at /.well-known/oauth-authorization-server so agents can discover your auth endpoints.

# Serve OAuth 2.0 Authorization Server Metadata at:
# https://example.com/.well-known/oauth-authorization-server
{
  "issuer": "https://example.com",
  "authorization_endpoint": "https://example.com/oauth/authorize",
  "token_endpoint": "https://example.com/oauth/token",
  "response_types_supported": ["code"],
  "grant_types_supported": ["authorization_code", "refresh_token"]
}
Failed OAuth Protected Resource +2 overall pts

No OAuth Protected Resource Metadata found at /.well-known/oauth-protected-resource and no WWW-Authenticate header on the homepage.

OAuth Protected Resource
HIGH

OAuth Protected Resource Metadata (RFC 9728) tells agents which authorization servers issue tokens for your APIs. Cloudflare's isitagentready.com checks this as part of Level 5 readiness.

Publish OAuth Protected Resource Metadata at /.well-known/oauth-protected-resource describing which authorization servers issue tokens for your APIs.

# Serve OAuth Protected Resource Metadata at:
# https://example.com/.well-known/oauth-protected-resource
{
  "resource": "https://api.example.com",
  "authorization_servers": ["https://example.com"],
  "bearer_methods_supported": ["header"]
}
Partial AI crawler directives +2 overall pts

No AI crawlers explicitly mentioned in robots.txt (implicit default allow applies).

AI crawler directives
MEDIUM

Major AI systems use dedicated crawlers (GPTBot, ClaudeBot, Amazonbot). Explicit directives signal whether you want your content included in AI training and search results.

Add a wildcard Allow: / or explicit AI user-agent directives to signal crawling intent.

robots.txt plain
# Add to your /robots.txt - explicit Allow for AI crawlers
User-agent: GPTBot
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: Google-Extended
Allow: /

User-agent: Amazonbot
Allow: /

User-agent: ChatGPT-User
Allow: /

User-agent: PerplexityBot
Allow: /
Failed Form label coverage +2 overall pts

0/1 form inputs have associated labels (1 missing).

Form label coverage
HIGH

AI agents interact with forms via the accessibility tree, which maps labels to inputs. Without proper label associations, AI agents cannot determine what data a form field expects, making form interaction unreliable or impossible.

Associate labels with all form inputs using <label for="id">, wrapping <label> elements, or aria-label/aria-labelledby attributes. AI agents rely on label associations to understand form field purposes. See w3.org/WAI/WCAG22/Understanding/labels-or-instructions.html for WCAG guidelines.

<!-- Explicit label association -->
<label for="email">Email address</label>
<input type="email" id="email" name="email">

<!-- Wrapping label -->
<label>
  Search
  <input type="search" name="q">
</label>

<!-- ARIA label for icon-only inputs -->
<input type="search" aria-label="Search the site">
Failed API Catalog (RFC 9727) +2 overall pts

No API Catalog found at /.well-known/api-catalog.

API Catalog (RFC 9727)
HIGH

API Catalog (RFC 9727 + RFC 9264 Linkset) gives agents a single discovery endpoint listing every API the site offers, with machine-readable links to OpenAPI specs (service-desc), human docs (service-doc), and health endpoints. Cloudflare's isitagentready.com scores this as part of Level 3 readiness.

Serve an RFC 9727 API Catalog at /.well-known/api-catalog with a linkset of service-desc, service-doc, and status links.

{
  "linkset": [
    {
      "anchor": "https://example.com/api/v1",
      "service-desc": [
        {"href": "https://example.com/openapi.json", "type": "application/openapi+json"}
      ],
      "service-doc": [
        {"href": "https://example.com/docs", "type": "text/html"}
      ],
      "status": [
        {"href": "https://example.com/health", "type": "application/json"}
      ]
    }
  ]
}
Failed Agent Skills index +2 overall pts

No Agent Skills index found at /.well-known/agent-skills/index.json or /.well-known/skills/index.json.

Agent Skills index
HIGH

Agent Skills Discovery (cloudflare/agent-skills-discovery-rfc v0.2.0) lets sites publish a directory of agent-callable skills with SHA-256 verifiable SKILL.md content. Cloudflare's isitagentready.com checks this for Level 4-5 readiness.

Publish an Agent Skills index per cloudflare/agent-skills-discovery-rfc v0.2.0 with top-level "$schema" and each skill's name, type (skill-md or archive), description, url, and digest (sha256:{64-hex}).

{
  "$schema": "https://raw.githubusercontent.com/cloudflare/agent-skills-discovery-rfc/main/schema/index.schema.json",
  "version": "0.2.0",
  "skills": [
    {
      "name": "search-products",
      "type": "skill-md",
      "description": "Search the product catalog",
      "url": "https://example.com/.well-known/agent-skills/search-products/SKILL.md",
      "digest": "sha256:abc123..."
    }
  ]
}
Failed WebMCP manifest +2 overall pts

No WebMCP manifest found at /.well-known/webmcp or /.well-known/webmcp.json.

WebMCP manifest
HIGH

A WebMCP manifest at /.well-known/webmcp.json enables pre-navigation discovery - AI agents can learn what tools your site offers before even loading the page.

Create a WebMCP manifest at /.well-known/webmcp.json with your tool definitions to enable pre-navigation agent discovery. Discovery is an active area of discussion in the WebMCP spec.

{
  "spec": "webmcp/0.1",
  "tools": [
    {
      "name": "search",
      "description": "Search products",
      "url": "/search",
      "method": "GET",
      "parameters": [
        {"name": "q", "type": "string", "description": "Search query"}
      ]
    }
  ]
}
Failed MCP Discovery +2 overall pts

No MCP discovery document found at /.well-known/mcp.json, /.well-known/mcp/server-card.json, or /.well-known/mcp/server-cards.json.

MCP Discovery
HIGH

The Model Context Protocol (MCP) by Anthropic is the standard for connecting AI assistants to external tools and data. A discovery document lets AI systems find and connect to your MCP server. SEP-1649 (modelcontextprotocol PR 2127) defines the new server-card.json schema with serverInfo, transport, and capabilities fields.

Create an MCP server card at /.well-known/mcp/server-card.json following SEP-1649 (serverInfo.name, transport, capabilities).

{
  "$schema": "https://modelcontextprotocol.io/schema/server-card.json",
  "name": "My Server",
  "serverInfo": {"name": "My Server", "version": "1.0.0"},
  "transport": {"type": "streamable-http", "endpoint": "https://bitdefender.nl/mcp"},
  "capabilities": {"tools": {"listChanged": false}}
}
Failed agents.json +2 overall pts

No agents.json found at /.well-known/agents.json or /agents.json.

agents.json
HIGH

agents.json provides a directory of AI agent endpoints on your site. It helps agent orchestration systems discover and connect to your available AI services.

Create an agents.json file at /.well-known/agents.json with your agent endpoint definitions.

agents.json json
{
  "agents": [
    {
      "name": "Support Agent",
      "description": "Handles customer inquiries",
      "url": "https://bitdefender.nl/agents/support",
      "protocol": "a2a"
    }
  ]
}
Partial Question-based headings +1 overall pts

1/5 H2 headings use question format ("Bent u al klant?"). Adding more question-based H2s would improve AI citation rates.

Question-based headings
MEDIUM

Question-based H2 headings dramatically improve AI citation likelihood. Research on 3M ChatGPT responses shows 78.4% of citations tied to questions came from H2 headings, and conversational Q&A format doubles overall citation rates.

Rewrite H2 headings as questions your audience asks. For example, instead of "Domain Authority Metrics" use "How does domain authority affect AI citations?". 78.4% of ChatGPT-cited pages use question-based H2 headings.

<!-- Instead of keyword-focused headings: -->
<h2>Domain Authority Metrics</h2>
<h2>SEO Best Practices</h2>

<!-- Use question-based headings: -->
<h2>How does domain authority affect AI citations?</h2>
<h2>What SEO practices improve AI visibility?</h2>
<h2>Why do AI systems prefer structured content?</h2>
Partial Semantic HTML elements +1 overall pts

Found 4/5 semantic elements: header, nav, footer, article/section.

Semantic HTML elements
MEDIUM

AI agents navigate pages using the accessibility tree, not visual layout. Semantic elements like <main>, <nav>, and <article> provide structural meaning that AI systems rely on to parse content.

Add missing semantic elements: main. Semantic HTML helps AI agents identify page regions and navigate content structure. See developer.mozilla.org/en-US/docs/Glossary/Semantics#semantics_in_html for semantic HTML documentation.

HTML html
<body>
  <header>
    <nav><!-- primary navigation --></nav>
  </header>
  <main>
    <article>
      <h1>Page Title</h1>
      <section><!-- content section --></section>
    </article>
  </main>
  <footer><!-- site footer --></footer>
</body>
Failed Button accessible names +1 overall pts

2/5 buttons have accessible names (3 missing).

Button accessible names
HIGH

AI agents invoke buttons by their accessible name in the accessibility tree. Without a discernible name, an AI agent cannot identify what a button does, making form submission and page interaction impossible.

Ensure all buttons have accessible names via text content, aria-label, aria-labelledby, or value attribute. AI agents cannot invoke unnamed buttons. See w3.org/WAI/WCAG22/Understanding/name-role-value.html for WCAG guidelines.

HTML html
<!-- Good: text content as name -->
<button>Submit form</button>

<!-- Good: aria-label for icon buttons -->
<button aria-label="Close dialog">
  <svg>...</svg>
</button>

<!-- Bad: empty button with no name -->
<button><img src="icon.svg"></button>
Fix with AI Skills
$ /plugin marketplace add bartwaardenburg/isagentready-skills

Detailed results

Agent Protocols

Weight 15% · 8 failed checkpoints

0/100
AI Content Discovery

Weight 30% · 3 failed, 1 partial

74/100
Security & Trust

Weight 15% · 2 failed checkpoints

79/100
Content & Semantics

Weight 20% · 2 failed, 3 partial

75/100
AI Search Signals

Weight 20% · 4 failed checkpoints

47/100
Supplemental evidence AI visitor test and training exposure. The score does not change.
AI Training Exposure

Does not affect the readiness score

Supplemental

No AI training protections detected. Your content may be freely used for AI model training.

Common Crawl presence Unknown

Could not determine the latest Common Crawl index.

Training crawler blocking Not found

No robots.txt found. Training crawlers can freely access your content.

TDMRep declaration Not found

No TDMRep file found at /.well-known/tdmrep.json. The TDM Reservation Protocol (W3C) lets you declare whether you reserve text and data mining rights. See w3.org/community/reports/tdmrep/CG-FINAL-tdmrep-20240510 for the specification.

ai.txt policy Not found

No ai.txt file found. ai.txt lets you declare AI usage preferences for your content.

Web Bot Auth Not found

No Web Bot Auth signature key directory found. Bots cannot prove their identity to origins via signed HTTP requests.

Next steps

DEVELOPER TOOLS

Scan and fix from your editor. Install the MCP server to scan, and AI skills to fix.

SCAN
$ claude mcp add isagentready-mcp -- npx -y isagentready-mcp
FIX
$ /plugin marketplace add bartwaardenburg/isagentready-skills
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