dot.vu shows strong AI visibility with an ACRI of 73/100, outperforming 75% of indexed domains. Compared to other developer sites (avg score: 57), dot.vu performs above the benchmark, suggesting strong competitive positioning in AI search. While the majority of content is server-rendered, the 30% ghost ratio suggests some content remains hidden from static crawlers. A 50.0× token bloat ratio means crawlers must process significantly more tokens to reach the actual content — a drag on extraction efficiency. Only 1 schema block is present — adding Organization, WebSite, and Breadcrumb schemas would significantly improve structured data coverage. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.
🧮 Score Transparency — How is this calculated?
📊 ACRI Sub-Scores (AI Readiness Detail)
dot.vu is more visible to Google than to AI models. There's room to improve AI discoverability to match your search reputation. ACRI measures technical crawler readiness. Read the methodology →
Why dot.vu ranks here
Fastest improvements
- Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
- Create an
llms.txtfile so AI crawlers can discover your content structure without heavy crawling. Generate llms.txt → - Run a full entropy audit to find which DOM regions waste the most tokens. Run Entropy Audit →
Traditional SEO
48/100 25 % of Global Score 🟢 High Confidence📝 Title Tag
Optimal range: 30–60 characters for SERP display.
📋 Meta Description
Optimal range: 120–160 characters for snippet control.
🔤 Heading Hierarchy
- ✗ Exactly 1 <h1> tag — found 12
- ✓ Has <h2> headings — found 7
- ✗ <h2> not before <h1>
🔍 Indexability
- ✓ Canonical tag present →
https://dot.vu/ - ✓ No noindex directive
- ✓ Meta viewport set
- ✓ HTML lang attribute →
en - ➖ Hreflang tags — N/A (single language site)
- ✓ Googlebot allowed by robots.txt
🌐 Social / OpenGraph
- ✓ og:title — The Leading Interactive Content Platform | Dot.vu | 2026
- ✓ og:description — Dot.vu is the leading Interactive Content platform that empowers brands to create Interactive Content that engages entertains and educates their customers.
- ✓ og:image — preview
- ✓ twitter:card — summary_large_image
📐 How the SEO Pillar score is calculated
SEO Pillar = Title (20 pts) + Meta Desc (20 pts) + Heading Hierarchy (20 pts) + Indexability (20 pts) + Social/OG (20 pts)
Each sub-score is derived from the checks above. Canonical tag, lang attribute, og:image, and a single H1 are the highest-impact items.
AI Readiness / GEO
56/100 40 % of Global Score 🟢 High ConfidenceThis pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.
Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.
🤖 Bot Access Matrix
👻 Rendering (Ghost Ratio) Docs
📊 Structure & Information Density Docs
🏷️ Schema Health Docs
Schema Coverage Map
📐 AI Efficiency Metrics Docs
Token Bloat Research
Multimodal Readiness
TDM Rights
🔥 Structural Entropy Check Research
🔬 AI-Crawler Simulation
See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
AI Answer Preview
NEWSee how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.
The LLM Interpretation
AI-VERIFIEDSEODiff AI analyzed the extracted content of dot.vu and produced this structured business intelligence. Fields marked SEMANTIC VOID indicate information the AI could not find — a critical gap in your site’s machine-readability.
🔧 Tech Stack
Performance & Speed
11/100 20 % of Global Score 🟢 High Confidence⏱️ Time to First Byte
Google considers <200 ms "good". AI crawlers may have even shorter timeouts.
📦 Page Weight
DOM nodes
HTML payload
🗄️ Cache & CDN
- ✓ Cache-Control header →
no-cache, max-age=0, must-revalidate, no-store - ✗ CDN cache status
- ✗ CDN detected
🔬 Tracker Tax
tracker scripts
third-party domains
token overhead
📐 How the Performance Pillar score is calculated
Perf Pillar = TTFB (35 pts) + Page Weight (25 pts) + Cache/CDN (20 pts) + Tracker Tax (20 pts)
TTFB <200 ms = full marks. DOM >3000 or payload >300 KB incurs heavy penalties. Tracker scripts beyond 5 reduce score.
Architecture & Trust
85/100 15 % of Global Score 🟢 High Confidence🗺️ Sitemap & Robots
- ✓ Sitemap declared in robots.txt →
https://dot.vu/sitemap.xml - ✓ Googlebot allowed
- ✓ GPTBot allowed
- ✓ ClaudeBot allowed
🔗 Linking
internal links
external links
🔒 Security & Trust
- ✓ HSTS header (Strict-Transport-Security)
- ✓ Content-Security-Policy header
- ✓ HTTP status 200 OK (got 200)
♿ Accessibility Signals
- ✓ HTML lang attribute → en
- ✓ Meta viewport for mobile
- ✗ Single H1 for screen readers
📐 How the Architecture Pillar score is calculated
Arch Pillar = Sitemap & Robots (30 pts) + Linking (25 pts) + Security (25 pts) + Accessibility (20 pts)
Having a valid sitemap, allowing AI bots, HSTS, and a good internal link count are the highest-impact items.
🏅 AI-Verified Trust Badge
Your site scores 48/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.
<a href="https://seodiff.io/radar/domains/dot.vu" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=dot.vu" alt="AI-Verified by SEODiff" width="280" height="52"></a>
💡 Paste in your site footer, GitHub README, or email signature. Badge updates automatically as your score changes.
� Deep Crawl Analysis 10 pages · Deep-10
Homepage scores 48, but internal pages average only 35 — a -13-point gap. Blogs, docs, and legacy content are dragging down AI readability site-wide.
Poorly formatted tables or pricing grids on 2 pages will be split incorrectly during RAG chunking, causing AI models to hallucinate prices and features.
| Page | Type | ACRI | Token Bloat | Words | Status |
|---|---|---|---|---|---|
| pricing | 60 | 499.3× | 2100 | ⚠️ RAG Fracture | |
| pricing | 60 | 485.6× | 549 | 💰 Pricing | |
| pricing | 60 | 221.7× | 4730 | 💰 Pricing | |
| pricing | 60 | 318.5× | 2633 | ⚠️ RAG Fracture | |
| pricing | 60 | 587.4× | 525 | 💰 Pricing | |
| pricing | 50 | 648.8× | 310 | 💰 Pricing | |
| product | 0 | 0.0× | 0 | ✓ | |
| blog | 0 | 0.0× | 0 | ✓ | |
| docs | 0 | 0.0× | 0 | ✓ | |
| social-proof | 0 | 0.0× | 0 | ✓ |
| Path | Pages | Avg ACRI | Ghost % | Bloat | Top Issue |
|---|---|---|---|---|---|
| /case-studies/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /contact/ | 1 | 60 | 1% | 587.5× | Bot Blocked |
| /integrations/ | 1 | 50 | 1% | 648.8× | Bot Blocked |
| /faq/ | 1 | 60 | 1% | 318.4× | Bot Blocked |
| /pricing/ | 1 | 60 | 1% | 499.3× | Bot Blocked |
| /about/ | 1 | 60 | 1% | 485.6× | Bot Blocked |
| /features/ | 1 | 60 | 1% | 221.7× | Bot Blocked |
| /products/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /blog/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
| /docs/ | 1 | 0 | 0% | 0.0× | Low AI Readiness |
Scores update automatically each month. Create a free account for on-demand re-crawls (3/month free).
🔌 API Access
Pull this data programmatically. All sub-page metrics are available via our public API.
curl https://seodiff.io/api/v1/deep10/domain/dot.vuGet your free API key — 100 requests/month included.
🔗 Similar developer Sites
Domains with a similar tech stack, industry, and AI readiness profile to dot.vu. Compare side-by-side.
| Domain | ACRI | AI Score | Tech Stack | Token Bloat | Schema | |
|---|---|---|---|---|---|---|
| dot.vu (this site) | 48 | 73 | Express | 151.2× | 1 | — |
| retrolinen.com | 73 | 79 | Express | 5.6× | 1 | Compare → |
| mobiletrain.org | 73 | 78 | Express | 2.0× | 0 | Compare → |
| jensonusa.com | 73 | 78 | Express | 2.3× | 0 | Compare → |
| karyakreasi.id | 73 | 77 | Express | 6.6× | 3 | Compare → |
| farmae.de | 73 | 87 | Express | 19.8× | 3 | Compare → |
📊 Semantic Share of Voice
How often would an AI cite dot.vu when users ask about topics in this domain's niche? We run entity queries through our 188k-page search index and measure citation probability.
Analyzing citation landscape…
Remediation Patches
COPY-PASTEAuto-generated code fixes tailored to dot.vu. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "WebSite",
"name": "Dot",
"url": "https://dot.vu",
"potentialAction": {
"@type": "SearchAction",
"target": "https://dot.vu/search?q={search_term_string}",
"query-input": "required name=search_term_string"
}
}
</script>
<!-- Move inline CSS to external stylesheets --> <link rel="stylesheet" href="/css/main.css"> <!-- Move inline scripts to external files with defer --> <script src="/js/app.js" defer></script> <!-- Remove duplicate navigation blocks --> <!-- Keep only ONE <nav> in the <header> --> <!-- Ensure <main> wraps your primary content --> <main> <!-- Your content here — this is what AI sees first --> </main>
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is Dot?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Add your answer here — describe what Dot does in 1-2 sentences."
}
},
{
"@type": "Question",
"name": "How does Dot work?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Explain the key features and how users interact with Dot."
}
}
]
}
</script>
Projected Impact
ROI EST.If you apply the patches above, here's the estimated improvement for dot.vu:
*Estimates based on SEODiff's scoring model. Actual results depend on implementation quality.
📋 Data Export
Download scores and metadata for audits, client reports, or CI/CD pipelines. Exports contain computed metrics only (no copyrighted content).
All data is generated automatically and updated with each crawl. JSON exports contain scores and metadata only (no copyrighted content).
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