mhu.edu 77 B
🛡️ SEO 75 🤖 GEO 88 ⚡ Perf 53 🏗️ Arch 83

mhu.edu — Global SEODiff Score 77/100

mhu.edu
📊

Registering an exceptional 87/100 on the AI-Crawler Reality Index, mhu.edu sits in the highest tier of AI extractability among indexed domains. Compared to other education sites (avg score: 57), mhu.edu performs above the benchmark, suggesting strong competitive positioning in AI search. The low ghost ratio (0%) confirms that what crawlers see matches what users see — a hallmark of strong SSR implementation. The 7.6× token bloat ratio falls within the normal range, though there is room to trim navigation, footer, and script overhead. Minimal structured data (1 block) limits the site's ability to communicate entity relationships to AI systems. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.

77
B — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Performance (53) is your bottleneck.
🎯 Top Fix: Add HSTS header → +2 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 25, 2026 · 📋 API
Does your site score higher than mhu.edu?
Run the same 40-signal audit on your own domain — free, instant results.
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)75 × 0.25 = 18.8
🤖 AI Readiness / GEO (40% weight)88 × 0.40 = 35.2
⚡ Performance (20% weight)53 × 0.20 = 10.6
🏗️ Architecture & Trust (15% weight)83 × 0.15 = 12.4
Weighted sum = 18.8 + 35.2 + 10.6 + 12.4
Global SEODiff Score = 77 (B)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
100
Rendering
avg 93
85
Structure
avg 35
42
Schema
avg 10
85
Tech Stack
avg 64
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 50%+
Rank #525949
-51 pts
Gap
AI (ACRI)
Top 1%
Score 87/100

mhu.edu ranks much higher on Google (Tranco Top 50%+) than in AI search (Top 1%). This is the 'Invisible Giant' pattern — implement the patches above to close the AI gap. ACRI measures technical crawler readiness. Read the methodology →

Why mhu.edu ranks here

Tech stackWordPress
Industryeducation
RenderingSSR
Schema coverage1 blocks
Token bloat7.6×

Fastest improvements

  • Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
  • Create an llms.txt file 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 →
🧪

JavaScript Rendering Check

We check what AI crawlers miss when they skip JavaScript execution.

Running headless browser to simulate AI extraction…
🛡️

Traditional SEO

75/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

53 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

123 chars
Good length

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 4
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://www.mhu.edu/
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en-US
  • ✗ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✓ og:title — Mars Hill University, near Asheville, North Carolina.
  • ✓ og:description — Mars Hill University is a private, liberal arts college, located near Asheville in the mountains of western North Carolina.
  • ✗ og:image
  • ✓ 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

88/100 40 % of Global Score 🟢 High Confidence

This pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.

🔗

Citation Alternatives

Research
💡
Insight: In the education sector, rndirectors.com (ACRI: 85) currently has stronger AI extractability. AI models tend to prefer sources with higher semantic structure and schema coverage. Domains with ACRI < 40 see 3.5× more hallucinations. Read the research →
mhu.edu
76
Your ACRI Score
85
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. rndirectors.com has schema coverage of 4 blocks and uses WordPress. Improve your score by implementing the remediation patches below.
📊 Side-by-Side Comparison →
🚨

Hallucination Risk

Research

Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.

Analyzing hallucination risk…

🤖 Bot Access Matrix

GPTBot (OpenAI)
Allowed
ClaudeBot (Anthropic)
Allowed
CCBot (Common Crawl)
Allowed
Google-Extended
Allowed
Googlebot
Allowed

👻 Rendering (Ghost Ratio) Docs

Ghost Ratio 0%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type SSR

📊 Structure & Information Density Docs

Structure Grade 85/100 — Excellent
Structured Elements 299 elements (299 lists, 0 rows, 0 headers)
Total Words1382
Raw Density21.6%

🏷️ Schema Health Docs

Organization Schema ✅ Present
Product / Service Schema ⚠️ Not Found
Total Schema Blocks1 block(s) — Basic (low value for AI)

Schema Coverage Map

3/7 schema types detected
✅ Organization
❌ Product/Service
✅ Breadcrumb
❌ FAQ
❌ Article
✅ WebSite
💡Product / Service schema missing. AI models don't know this is a SaaS product. Add Product or SoftwareApplication schema so AI understands what you offer and can surface pricing/features.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.

📐 AI Efficiency Metrics Docs

74
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability74/100 — AI models can easily extract answers from this page
Crawl CostLow (30/100) — efficient for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

13%
🗑️ 87%
Useful Content (17.4 KB)Bloat (114.9 KB)
Token Bloat Ratio7.6× — Normal

Multimodal Readiness

Visual ContextNo images detected
Image Alt Coverage0 / 0 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 86.8% · SNR: 0.15 · Signal: 4465 / Noise: 29413 tokens

🔬 AI-Crawler Simulation

See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.

🌐
This is what humans see — styled, branded, visual.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
🤖

AI Answer Preview

NEW

See how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.

Simulating AI extraction…
🧠

The LLM Interpretation

AI-VERIFIED

A local LLM (mlx-community/Qwen2.5-7B-Instruct-4bit) analyzed the extracted content of mhu.edu 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.

Core Offering
Private liberal arts college education
Target Audience
High school students and their families
Pricing Model
Not specified
Model: mlx-community/Qwen2.5-7B-Instruct-4bit · Analyzed: 2026-02-26 · Data extracted from the site’s main content via strict JSON prompting.

🔧 Tech Stack

FrameworkWordPress
AI-Readiness Score85/100
Servernginx
CDN
HTTP Status200
Load Time1359 ms
Raw HTML Size132.3 KB
Visible Text Size17.4 KB

Performance & Speed

53/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

1359 ms
Slow — bots may time out or deprioritise

Google considers <200 ms "good". AI crawlers may have even shorter timeouts.

📦 Page Weight

1425
DOM nodes
132 KB
HTML payload
Moderate weight — acceptable for most scenarios

🗄️ Cache & CDN

  • ✓ Cache-Control header → max-age=3, must-revalidate
  • ✗ CDN cache status
  • ✗ CDN detected

🔬 Tracker Tax

1
tracker scripts
1
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
googletagmanager.com
📐 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

83/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://www.mhu.edu/sitemap_index.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

397
internal links
20
external links
Good internal linking — helps crawlers discover content

🔒 Security & Trust

  • ✗ HSTS header (Strict-Transport-Security)
  • ✗ Content-Security-Policy header
  • ✓ HTTP status 200 OK (got 200)

♿ Accessibility Signals

  • ✓ HTML lang attribute → en-US
  • ✓ 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 76/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for mhu.edu
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/mhu.edu" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=mhu.edu" 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 1 pages · Deep-10

Homepage ACRI
76
Single-page score
-4
Consistent readability
Δ delta
Site-Wide ACRI
72
Avg across 1 pages · Range 72–72
Total Words
1230
Avg Bloat
19.5×
Ext. Citations
17
Page Type ACRI Token Bloat Words Status
https://mhu.edu/about
About - Mars Hill University
pricing 72 19.5× 1230 💰 Pricing
🔗
Outbound External Citations
17 unique external domains cited across 1 pages
blazedigitalbrands.com ×1
instagram.com ×1
digitalnc.org ×1
jobs.appone.com ×1
youtube.com ×1
moodle.mhu.edu ×1
twitter.com ×1
my.mhu.edu ×1
🔄 Re-Crawl & Update 📡 Track this Domain

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/mhu.edu

Get your free API key — 100 requests/month included.

🔗 Similar education Sites

Domains with a similar tech stack, industry, and AI readiness profile to mhu.edu. Compare side-by-side.

Domain ACRI AI Score Tech Stack Token Bloat Schema
mhu.edu (this site) 76 87 WordPress 7.6× 1
carlow.edu 76 88 WordPress 7.5× 1 Compare →
cybersecurityguide.org 76 87 WordPress 8.2× 1 Compare →
mku.ac.ke 76 88 WordPress 7.0× 1 Compare →
concordia.ab.ca 75 88 WordPress 7.1× 1 Compare →
hyacinthbloom.com 77 84 WordPress 8.1× 1 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to mhu.edu. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →

Add FAQ Schema
Medium Impact ⏱ 10 min
FAQ schema lets AI models directly extract Q&A pairs. This is the easiest way to get featured in AI responses.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Mhu?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Mhu does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Mhu work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Mhu."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for mhu.edu:

Current Score
87
Projected Score
93
Improvement
+6 pts
Reduce token bloat +3 pts
Add FAQ schema +3 pts

*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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🧭 Self-Diffing (Private Layer)

For owned domains, combine this world snapshot with private drift + regression history.
Template Drift
Track in My Site
Drift → Traffic Impact
In development coming soon
Regression Incidents
Track in My Site
Internal Linking
Deep Audit graph
Semantic Structure
GEO view in Deep Audit
Content Quality
Thin/duplicate tracking

🕒 History

Score over timeAvailable in My Site history
Drift eventsTemplate timeline + incidents
Drift → Revenue AttributionComing soon
Schema/rendering/extractability changesTracked per scan in project history