Changes since selected scan Not comparable because detailed evidence is unavailable
Result summary
Readiness profiles
Methodology 2026-08-29Measured stable-core coverage
82/100
Methodology grade
A
37 core checkpoints assessed
28
Passed
4
Partial
5
Failed
12
Skipped
Strongest category
Security & Trust
Weakest category
AI Search Signals
Action plan
Priority actions
Highest-impact implementation details
3 prioritized 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
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
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
HIGHLink 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.
# 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://triple.nl/ | grep -i '^link:'
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
HIGHAuthor 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.
<!-- 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://triple.nl/team/jane-smith"
}
}
</script>
<!-- Option 2: Meta tag -->
<meta name="author" content="Jane Smith">
<!-- Option 3: Linked author -->
<a rel="author" href="https://triple.nl/team/jane-smith">Jane Smith</a>
Detailed results
Agent Protocols
Weight 15%
Not assessed
No score-impacting checkpoints
5 bonus opportunities and 3 informational findings; do not affect the core score
Core score
0/100
No score-impacting checkpoints
5 bonus opportunities and 3 informational findings; do not affect the core score
AI Content Discovery
Weight 30%
Needs attention
1 failed, 1 partial score-impacting checkpoints
6 bonus opportunities; do not affect the core score
Core score
85/100
1 failed, 1 partial score-impacting checkpoints
6 bonus opportunities; do not affect the core score
Security & Trust
Weight 15%
Ready
All score-impacting checkpoints passed
Core score
100/100
All score-impacting checkpoints passed
Content & Semantics
Weight 20%
Needs attention
2 failed, 3 partial score-impacting checkpoints
Core score
80/100
2 failed, 3 partial score-impacting checkpoints
AI Search Signals
Weight 20%
Needs attention
2 failed score-impacting checkpoints
Core score
68/100
2 failed score-impacting checkpoints
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
Supplemental
Does not affect the readiness score
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
/plugin marketplace add bartwaardenburg/isagentready-skills
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- Detailed score breakdown per category
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