Result summary
Measured stable-core coverage
64/100
Methodology grade
C
Methodology 2026-08-29
33 core checkpoints assessed
Readiness profiles
Select a profile to filter the detailed results.
Action plan
Priority actions
Highest-impact implementation details
3 prioritized actions
Prioritized by exact impact on the overall stable-core score.
Failed
JSON-LD present
+6 overall pts
No valid JSON-LD blocks with schema.org @context found.
JSON-LD present
HIGHJSON-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.
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Your Company",
"url": "https://nluug.nl",
"logo": "https://nluug.nl/logo.png"
}
</script>
Failed
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
HIGHCertain 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.
<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
Endpoint check timed out
+5 overall pts
Request timed out - the site may be blocking automated access.
Detailed results
Agent Protocols
Weight 15% · No applicable checkpoints · 5 bonus opportunities
Not assessed
Weight 15% · No applicable checkpoints · 5 bonus opportunities
AI Content Discovery
Weight 30% · 2 failed, 1 partial · 5 bonus opportunities
71/100
Weight 30% · 2 failed, 1 partial · 5 bonus opportunities
Security & Trust
Weight 15% · 1 failed checkpoint
93/100
Weight 15% · 1 failed checkpoint
Content & Semantics
Weight 20% · 2 failed, 2 partial
86/100
Weight 20% · 2 failed, 2 partial
AI Search Signals
Weight 20% · 4 failed, 1 partial
9/100
Weight 20% · 4 failed, 1 partial
AI visitor test
We let an AI try common visitor tasks to show what works and where it gets stuck.
Can an AI understand this website?
UnavailableThis check is temporarily unavailable.
Can an AI find a useful action to take?
UnavailableThis check is temporarily unavailable.
AI Training Exposure
Does not affect the readiness score
Supplemental
Does not affect the readiness score
No AI training protections detected. Your content may be freely used for AI model training.
Could not determine the latest Common Crawl index.
No training crawlers are blocked in robots.txt. All known AI training bots can access your content.
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.
No ai.txt file found. ai.txt lets you declare AI usage preferences for your content.
No Web Bot Auth signature key directory found. Bots cannot prove their identity to origins via signed HTTP requests.
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
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
/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
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