webreus.nl

Item: webreus.nl
Rating: 32

Compare

Scan history

Scanned 2026-05-18 10:51 UTC

2026-08-29 11:58 UTC 45/100 Compare

2026-05-18 10:51 UTC 32/100 Compare

2026-03-03 13:14 UTC 38/100 Compare

2026-03-01 15:26 UTC 40/100 Compare

SCAN HISTORY Scanned 2026-05-18 10:51 UTC

2026-08-29 11:58 UTC 45/100 Compare

2026-05-18 10:51 UTC 32/100 Compare

2026-03-03 13:14 UTC 38/100 Compare

2026-03-01 15:26 UTC 40/100 Compare

Result summary

Readiness profiles

Methodology legacy

Measured coverage

32/100

Methodology grade

48 checkpoints assessed

Passed

Partial

Failed

Skipped

Strongest category

Content & Semantics

Weakest category

Agent Protocols

Action plan

Priority actions Highest-impact implementation details

3 prioritized actions

Prioritized by exact impact on the overall stable-core score.

JSON-LD present +6 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. Schema markup provides a 73% higher selection rate in Google AI Overviews.

JSON-LD html

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company",
  "url": "https://webreus.nl",
  "logo": "https://webreus.nl/logo.png"
}
</script>

Sources

High-value schema types +6 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>

Sources

Organization / WebSite schema +4 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://webreus.nl",
  "logo": "https://webreus.nl/logo.png",
  "sameAs": [
    "https://twitter.com/yourcompany",
    "https://linkedin.com/company/yourcompany"
  ]
}
</script>

Sources

Fix with AI Skills

$ /plugin marketplace add bartwaardenburg/isagentready-skills

Detailed results

Agent Protocols Weight 15% Needs attention

9 failed checkpoints

0/100

WebMCP Declarative API: Failed

API Catalog (RFC 9727): Failed

Agent Skills index: Failed

WebMCP manifest: Failed

A2A Agent Card: Failed

MCP Discovery: Failed

OpenAPI / API documentation: Failed

agents.json: Failed

Interactive Surface Coverage: Failed

AI Content Discovery Weight 30% Needs attention

6 failed, 1 partial

41/100

robots.txt present: Passed

Content Signals (robots.txt): Failed

AI crawler directives: Partial

XML Sitemap: Failed

llms.txt: Failed

Meta robots / X-Robots-Tag: Passed

Content freshness signals: Failed

Content negotiation (text/markdown): Failed

HTTP bot accessibility: Passed

Link response headers: Failed

Security & Trust Weight 15% Needs attention

4 failed checkpoints

48/100

HTTPS: Passed

Auto-submit Risk Assessment: Passed

OAuth Discovery: Failed

OAuth Protected Resource: Failed

HSTS header: Failed

Content-Security-Policy: Failed

X-Content-Type-Options: Passed

Frame protection: Passed

CORS configuration: Passed

Referrer-Policy: Passed

Content & Semantics Weight 20% Needs attention

2 failed, 5 partial

64/100

Server-side rendered content: Passed

Form field autocomplete: Failed

Keyboard navigability: Passed

Document title: Partial

Button accessible names: Passed

aria-hidden misuse: Passed

Heading hierarchy: Partial

Semantic HTML elements: Failed

Accessible landmarks & ARIA: Partial

Image alt text: Passed

Language attribute: Passed

Descriptive link texts: Passed

Question-based headings: Partial

Form label coverage: Partial

AI Search Signals Weight 20% Needs attention

5 failed checkpoints

0/100

JSON-LD present: Failed

Organization / WebSite schema: Failed

High-value schema types: Failed

FAQPage schema: Failed

Author attribution: Failed

AI Training Exposure Supplemental

Does not affect the readiness score

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.

Developer Tools

Scan and fix from your editor

Install our MCP server to scan any website from your terminal. Pair it with AI agent skills to fix failing checks automatically.

Scan any website directly from your terminal
Fix failing checks with AI agent skills
Re-scan to verify improvements

SCAN

claude mcp add isagentready-mcp -- npx -y isagentready-mcp

codex mcp add isagentready-mcp -- npx -y isagentready-mcp

gemini mcp add isagentready-mcp -- npx -y isagentready-mcp

docker run -i --rm ghcr.io/bartwaardenburg/isagentready-mcp

FIX

/plugin marketplace add bartwaardenburg/isagentready-skills

git clone https://github.com/bartwaardenburg/isagentready-skills.git ~/.cursor/skills/isagentready-skills

git clone https://github.com/bartwaardenburg/isagentready-skills.git ~/.agents/skills/isagentready-skills

git clone https://github.com/bartwaardenburg/isagentready-skills.git ~/.codeium/windsurf/skills/isagentready-skills

git clone https://github.com/bartwaardenburg/isagentready-skills.git ~/.agents/skills/isagentready-skills

gemini skills install https://github.com/bartwaardenburg/isagentready-skills.git

git clone https://github.com/bartwaardenburg/isagentready-skills.git ~/.config/agents/skills/isagentready-skills

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Detailed score breakdown per category
Prioritized improvement recommendations
Step-by-step implementation guide