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Scan history Scanned 2026-08-29 15:36 UTC
55/100 Current
45/100 Compare
54/100 Compare
59/100 Compare

Result summary

Measured stable-core coverage

55/100

Methodology grade

C

Methodology 2026-08-29

36 core checkpoints assessed

Find
4/7 passed
Read
14/22 passed
Act
2/7 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 JSON-LD present +7 overall pts

No valid JSON-LD blocks with schema.org @context found.

JSON-LD present
HIGH

JSON-LD is the preferred format for structured data by Google and AI search engines. It tells AI systems exactly what your page is about using a standardized vocabulary.

Add at least one <script type="application/ld+json"> block with "@context": "schema.org" describing your organization or page content. This gives agents an unambiguous, machine-readable description of your page and makes it eligible for rich results in search.

JSON-LD html 
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company",
  "url": "https://lumc.nl",
  "logo": "https://lumc.nl/logo.png"
}
</script>
Sources
Failed High-value schema types +7 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 Bing and give agents typed, unambiguous entities to extract instead of inferring from prose. Their effect on AI-search citations is indirect, via the search indexes that feed products like ChatGPT and Perplexity.

Add JSON-LD markup for content-appropriate types like Article, Product, SoftwareApplication, FAQPage, LocalBusiness, Service, Event, or VideoObject so agents and search engines can identify your content type and extract structured facts reliably.

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>
Sources
Failed XML Sitemap +6 overall pts

No valid XML sitemap found. Checked: lumc.nl/sitemap.xml, lumc.nl/sitemap_index.xml.

XML Sitemap
HIGH

Sitemaps help AI crawlers discover all your pages efficiently. Without one, crawlers may miss important content or waste time discovering your site structure.

Create an XML sitemap and reference it in robots.txt with a Sitemap: directive.

sitemap.xml html 
<!-- /sitemap.xml -->
<?xml version="1.0" encoding="UTF-8"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
  <url>
    <loc>https://lumc.nl/</loc>
    <lastmod>2025-01-15</lastmod>
    <changefreq>weekly</changefreq>
    <priority>1.0</priority>
  </url>
  <url>
    <loc>https://lumc.nl/about</loc>
    <lastmod>2025-01-10</lastmod>
  </url>
</urlset>

# Add to /robots.txt:
Sitemap: https://lumc.nl/sitemap.xml
Sources
Failed Organization / WebSite schema +5 overall pts

No Organization or WebSite schema type found in JSON-LD.

Organization / WebSite schema
HIGH

Organization and WebSite schemas establish your brand identity in the knowledge graph. AI systems use these to attribute content, display rich results, and build entity relationships.

Add a JSON-LD block with @type "Organization" or "WebSite" including at least "name" and "url" properties.

JSON-LD html 
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company",
  "url": "https://lumc.nl",
  "logo": "https://lumc.nl/logo.png",
  "sameAs": [
    "https://twitter.com/yourcompany",
    "https://linkedin.com/company/yourcompany"
  ]
}
</script>
Sources
Failed Content freshness signals +4 overall pts

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

Content freshness signals
HIGH

AI systems prefer recent content, and several engines surface newer pages more often. 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.

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)
Sources
Failed Link response headers +4 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://lumc.nl/ | grep -i '^link:'
Sources
Failed Author attribution +3 overall pts

No author attribution found. Agents and search engines cannot tell who stands behind this content or link it to a known author entity.

Author attribution
HIGH

Author attribution gives agents and search engines a clear, machine-readable signal of who stands behind the content and links it to a known entity. This supports trust and provenance (E-E-A-T) and lets systems attribute the content to its author.

Add author information using JSON-LD (preferred), <meta name="author">, or <a rel="author">. Clear authorship is a trust and provenance signal for agents and search engines.

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://lumc.nl/team/jane-smith"
  }
}
</script>

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

<!-- Option 3: Linked author -->
<a rel="author" href="https://lumc.nl/team/jane-smith">Jane Smith</a>
Sources
Failed Trust anchor pages +3 overall pts

Verified none; missing or thin: about, contact, privacy.

Trust anchor pages
HIGH

Agents check about, contact and privacy pages to verify a business is legitimate and to answer contact questions before recommending it. Thin or missing trust pages read as an anonymous site.

Publish real /about, /contact and /privacy pages (or localized equivalents linked from the home page) with at least 500 characters of content each, and link them from the footer so agents and crawlers can find them.

Sources
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"]
}
Sources
Failed Agent Auth Readiness +2 overall pts

Agent auth readiness issues: missing PKCE S256 support, missing scoped permissions metadata, missing protected-resource metadata or WWW-Authenticate hint, missing valid auth.md, missing agent-safe OAuth grant declaration.

Agent Auth Readiness
HIGH

Agents need more than a login page. They need discoverable auth metadata, scoped permissions, PKCE support, and a concise walkthrough that explains how to obtain and use credentials safely.

Publish OAuth metadata with PKCE S256 and scopes, OAuth Protected Resource metadata, WWW-Authenticate hints on protected endpoints, and an /auth.md walkthrough for agents.

auth.md plain 
# /auth.md
# Authentication for agents

Use OAuth 2.0 authorization code with PKCE S256. Request the narrowest scope for the task. Protected API endpoints return WWW-Authenticate with resource metadata.
Sources
Failed Form field autocomplete +2 overall pts

0/1 applicable form inputs have autocomplete attributes (1 missing).

Form field autocomplete
HIGH

The autocomplete attribute tells AI agents and browsers what type of data a field expects (email, name, address). This semantic hint helps AI agents fill forms accurately without guessing field purposes from visual context.

Add autocomplete attributes to form inputs so AI agents and browsers understand the expected data type. Use standard values like "email", "name", "tel", "street-address". See html.spec.whatwg.org/multipage/form-control-infrastructure.html#autofill for the full list. 

<input type="email" name="email" autocomplete="email">
<input type="text" name="name" autocomplete="name">
<input type="tel" name="phone" autocomplete="tel">
<input type="text" name="address" autocomplete="street-address">
Sources
Failed Question-based headings +2 overall pts

None of the 9 H2 headings use question format. AI systems often treat a question H2 as a prompt and cite the answer beneath it.

Question-based headings
HIGH

AI systems often treat an H2 as a prompt and the paragraph beneath it as the answer. A study of 3M ChatGPT responses found that, among citations tied to questions, 78.4% came from headings, and cited content was about twice as likely to contain a question mark (Kevin Indig / Growth Memo).

Rewrite H2 headings as questions your audience asks. For example, instead of "Domain Authority Metrics" use "How does domain authority affect AI citations?". A study of 3M ChatGPT responses found 78.4% of question-related citations came from headings (Kevin Indig / Growth Memo). 

<!-- 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>
Sources
Failed Form label coverage +1 overall pts

1/3 form inputs have associated labels (2 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">
Sources
Partial Semantic HTML elements +1 overall pts

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

Semantic HTML elements
MEDIUM

Browser agents may combine the DOM, accessibility tree, and screenshots. Semantic elements like <main>, <nav>, and <article> provide durable structural meaning across those representations.

Add missing semantic elements: article or section. 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>
Sources
Partial Image alt text +1 overall pts

12/15 images have alt attributes (3 missing).

Image alt text
MEDIUM

Some browser agents can inspect screenshots, but image understanding varies by access mode. Descriptive alt text provides a durable machine-readable description of image content and context.

Add descriptive alt text to all images. Use alt="" for purely decorative images. Missing alt attributes prevent AI agents from understanding image content. See w3.org/WAI/WCAG22/Understanding/non-text-content.html for WCAG guidelines on non-text content.

HTML html 
<!-- Descriptive alt text for meaningful images -->
<img src="chart.png" alt="Revenue growth chart showing 40% increase in Q4 2025">

<!-- Empty alt for purely decorative images -->
<img src="divider.svg" alt="">
Sources
Partial Keyboard navigability +1 overall pts

2 keyboard accessibility issues found: 1 clickable div(s) without tabindex, 1 interactive element(s) missing ARIA role.

Keyboard navigability
MEDIUM

AI agents navigate pages using keyboard-style interactions via the accessibility tree. Positive tabindex values break natural focus order, and missing focusable elements on interactive widgets prevent AI agents from discovering and operating controls.

Avoid positive tabindex values (use tabindex="0" or "-1" instead), use native interactive elements (<button>, <a>) instead of divs with onclick handlers, and add proper ARIA roles to custom interactive widgets. See w3.org/WAI/WCAG22/Understanding/focus-order.html for WCAG focus order guidelines. 

<!-- Bad: positive tabindex breaks natural order -->
<div tabindex="5" onclick="doSomething()">Click me</div>

<!-- Good: native elements with natural focus -->
<button onclick="doSomething()">Click me</button>

<!-- Good: custom widget with role and tabindex="0" -->
<div role="button" tabindex="0" onclick="doSomething()">Click me</div>
Sources
Fix with AI Skills
$ /plugin marketplace add bartwaardenburg/isagentready-skills

Detailed results

Agent Protocols

Weight 15% · No applicable checkpoints · 5 bonus opportunities

Not assessed
AI Content Discovery

Weight 30% · 3 failed checkpoints · 6 bonus opportunities

65/100
Security & Trust

Weight 15% · 2 failed checkpoints · 1 bonus opportunity

79/100
Content & Semantics

Weight 20% · 3 failed, 3 partial

78/100
AI Search Signals

Weight 20% · 5 failed checkpoints

0/100
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 training crawlers are blocked in robots.txt. All known AI training bots can 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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