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Scan history Scanned 2026-08-29 16:20 UTC
57/100 Current
54/100 Compare
60/100 Compare
65/100 Compare

Result summary

Measured stable-core coverage

57/100

Methodology grade

C

Methodology 2026-08-29

38 core checkpoints assessed

Find
4/7 passed
Read
13/24 passed
Act
3/7 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 OpenAPI / API documentation +15 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"}}
        ]
      }
    }
  }
}
Sources
Failed XML Sitemap +4 overall pts

No valid XML sitemap found. Checked: mauritshuis.nl/sitemap.xml, mauritshuis.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://mauritshuis.nl/</loc>
    <lastmod>2025-01-15</lastmod>
    <changefreq>weekly</changefreq>
    <priority>1.0</priority>
  </url>
  <url>
    <loc>https://mauritshuis.nl/about</loc>
    <lastmod>2025-01-10</lastmod>
  </url>
</urlset>

# Add to /robots.txt:
Sitemap: https://mauritshuis.nl/sitemap.xml
Sources
Failed High-value schema types +4 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 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://mauritshuis.nl/ | grep -i '^link:'
Sources
Failed Entity linking (@id) +2 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": "mauritshuis.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://mauritshuis.nl/#organization",
      "name": "Your Company",
      "url": "https://mauritshuis.nl"
    },
    {
      "@type": "WebSite",
      "@id": "https://mauritshuis.nl/#website",
      "name": "Your Site",
      "url": "https://mauritshuis.nl",
      "publisher": { "@id": "https://mauritshuis.nl/#organization" }
    }
  ]
}
</script>
Sources
Failed Author attribution +2 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://mauritshuis.nl/team/jane-smith"
  }
}
</script>

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

<!-- Option 3: Linked author -->
<a rel="author" href="https://mauritshuis.nl/team/jane-smith">Jane Smith</a>
Sources
Failed Trust anchor pages +2 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
Partial Content freshness signals +1 overall pts

Only HTTP Last-Modified header found. This is a server-level signal - add content-level dates (dateModified in JSON-LD or article:modified_time meta tag) for stronger freshness signals.

Content freshness signals
MEDIUM

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 a dateModified property to your JSON-LD structured data or an article:modified_time meta tag, so AI systems can read when the content was last updated.

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 Image alt text +1 overall pts

3/17 images have alt attributes (14 missing).

Image alt text
HIGH

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
Failed Form field autocomplete +1 overall pts

0/4 applicable form inputs have autocomplete attributes (4 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 +1 overall pts

None of the 10 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
Partial Heading hierarchy +1 overall pts

Single <h1> present but heading levels are skipped (e.g. <h1> followed by <h3>).

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>
Sources
Partial Schema validation +1 overall pts

Minor validation issues: WebSite missing required properties: name; Organization has empty required fields: name.

Schema validation
MEDIUM

Invalid structured data is ignored by search engines and AI systems. Validation errors mean your markup effort provides zero benefit - properly structured data is essential.

Fix the structural issues in your JSON-LD to ensure maximum compatibility with AI systems.

Sources
Partial aria-hidden misuse +1 overall pts

1 focusable element(s) found inside aria-hidden="true" containers. These elements are invisible in the accessibility tree but can still receive focus.

aria-hidden misuse
MEDIUM

aria-hidden="true" removes elements from the accessibility tree. When applied to the <body> or to focusable elements, it corrupts the tree that AI agents navigate, causing them to miss content or encounter invisible controls.

Ensure no focusable elements (links, buttons, inputs) are inside aria-hidden="true" containers. AI agents encounter these as invisible-yet-focusable controls, causing navigation confusion. Either remove the focusable elements or the aria-hidden attribute. See developer.mozilla.org/en-US/docs/Web/Accessibility/ARIA/Attributes/aria-hidden for documentation. 

<!-- Bad: focusable element inside aria-hidden -->
<div aria-hidden="true">
  <button>Hidden but focusable</button>
</div>

<!-- Good: only decorative content inside aria-hidden -->
<div aria-hidden="true">
  <span class="icon">★</span>
</div>

<!-- Good: use inert instead for temporarily hidden sections -->
<div inert>
  <button>Properly hidden and non-focusable</button>
</div>
Sources
Partial HSTS header +1 overall pts

HSTS active with max-age=31536000. If you serve content on subdomains, consider adding includeSubDomains.

HSTS header
MEDIUM

HSTS prevents protocol downgrade attacks by telling browsers to always use HTTPS. AI agents that follow redirects benefit from HSTS as it eliminates insecure initial connections.

If your site uses subdomains, adding includeSubDomains ensures they are also protected by HSTS.

Server config plain 
# Nginx
add_header Strict-Transport-Security "max-age=31536000; includeSubDomains; preload" always;

# Apache (.htaccess)
Header always set Strict-Transport-Security "max-age=31536000; includeSubDomains; preload"
Sources
Partial Semantic HTML elements +0 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 Form label coverage +0 overall pts

5/8 form inputs have associated labels (3 missing).

Form label coverage
MEDIUM

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 Dynamic widget state +0 overall pts

Detected 1 dynamic widget(s), 6 ARIA state attribute(s), and 0 live region(s).

Dynamic widget state
MEDIUM

Agents operate interactive widgets through the accessibility tree. Expandable panels, tabs, menus, switches, dialogs, and async status areas need explicit state so agents can tell what is open, selected, checked, current, or updating.

Expose dynamic widget state with aria-expanded, aria-selected, aria-checked, aria-current, aria-pressed, aria-controls, and aria-live or role="status" for async updates. 

<button aria-expanded="false" aria-controls="filters">Filters</button>
<section id="filters" hidden>...</section>
<div role="status" aria-live="polite"></div>
Sources
Fix with AI Skills
$ /plugin marketplace add bartwaardenburg/isagentready-skills

Detailed results

Agent Protocols

Weight 15% · 1 failed checkpoint · 5 bonus opportunities

0/100
AI Content Discovery

Weight 30% · 2 failed, 1 partial · 5 bonus opportunities

70/100
Security & Trust

Weight 15% · 1 partial checkpoint

95/100
Content & Semantics

Weight 20% · 3 failed, 5 partial

66/100
AI Search Signals

Weight 20% · 4 failed, 1 partial

42/100
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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