uni-augsburg.de struggles with AI visibility, recording a critical ACRI of 15/100 — AI crawlers face significant hurdles extracting its content. Compared to other education sites (avg score: 57), uni-augsburg.de is trailing the benchmark, indicating room for competitive improvement. Its server-rendered architecture ensures AI crawlers receive complete HTML on first request, a key advantage for extractability. A tight 2.5× token bloat ratio reflects disciplined markup: minimal noise between the crawler and the content it needs. Zero schema blocks puts this site at a disadvantage in knowledge graph and AI-answer pipelines that rely on explicit structured data. Some AI crawlers are permitted while others are blocked — a mixed robots.txt policy that limits visibility in certain AI ecosystems.
🧮 Score Transparency — How is this calculated?
📊 ACRI Sub-Scores (AI Readiness Detail)
uni-augsburg.de punches above its weight in AI — AI visibility exceeds Google ranking. This is a competitive moat worth protecting. ACRI measures technical crawler readiness. Read the methodology →
Why uni-augsburg.de ranks here
Fastest improvements
- Allow GPTBot in robots.txt so AI crawlers can access your pages (see Crawl Access).
- Allow ClaudeBot (many assistants rely on it) — blocking it often correlates with “AI invisibility.”
- Add basic Organization and WebSite JSON-LD to fix “0 schema blocks” (see Schema Coverage).
- 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
37/100 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 2
- ✓ Has <h2> headings — found 11
- ✗ <h2> not before <h1>
🔍 Indexability
- ✗ Canonical tag present
- ✓ No noindex directive
- ✓ Meta viewport set
- ✓ HTML lang attribute →
de - ✗ Hreflang tags
- ✓ Googlebot allowed by robots.txt
🌐 Social / OpenGraph
- ✗ og:title
- ✗ og:description
- ✗ og:image
- ✗ twitter:card
📐 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
85/100 40 % of Global Score 🟡 Medium 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
Allow: / under User-agent: GPTBot in your robots.txt.📊 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.
🔧 Tech Stack
Performance & Speed
34/100 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 →
max-age=0, no-cache, no-store, must-revalidate, private - ✗ 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
100/100 15 % of Global Score 🟢 High Confidence🗺️ Sitemap & Robots
- ✓ Sitemap declared in robots.txt →
http://uni-augsburg.de/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 → de
- ✓ 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 69/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.
<a href="https://seodiff.io/radar/domains/uni-augsburg.de" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=uni-augsburg.de" 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.
🔗 Similar education Sites
Domains with a similar tech stack, industry, and AI readiness profile to uni-augsburg.de. Compare side-by-side.
| Domain | ACRI | AI Score | Tech Stack | Token Bloat | Schema | |
|---|---|---|---|---|---|---|
| uni-augsburg.de (this site) | 69 | 15 | Django | 2.5× | 0 | — |
| moecdc.gov.np | 71 | 79 | Django | 2.5× | 0 | Compare → |
| therqa.com | 71 | 80 | Django | 1.6× | 0 | Compare → |
| kannuruniversity.ac.in | 72 | 80 | Django | 1.9× | 0 | Compare → |
| namdu.uz | 72 | 82 | Django | 1.7× | 0 | Compare → |
| esaral.com | 62 | 74 | Django | 2.5× | 0 | Compare → |
Remediation Patches
COPY-PASTEAuto-generated code fixes tailored to uni-augsburg.de. 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": "Organization",
"name": "Uni-augsburg",
"url": "https://uni-augsburg.de",
"logo": "https://assets.uni-augsburg.de/static/unia/img/unia_favicon.ico",
"sameAs": []
}
</script>
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "WebSite",
"name": "Uni-augsburg",
"url": "https://uni-augsburg.de",
"potentialAction": {
"@type": "SearchAction",
"target": "https://uni-augsburg.de/search?q={search_term_string}",
"query-input": "required name=search_term_string"
}
}
</script>
User-agent: GPTBot Allow: / User-agent: ChatGPT-User Allow: /
User-agent: ClaudeBot Allow: / User-agent: anthropic-ai Allow: /
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is Uni-augsburg?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Add your answer here — describe what Uni-augsburg does in 1-2 sentences."
}
},
{
"@type": "Question",
"name": "How does Uni-augsburg work?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Explain the key features and how users interact with Uni-augsburg."
}
}
]
}
</script>
Projected Impact
ROI EST.If you apply the patches above, here's the estimated improvement for uni-augsburg.de:
*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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