mtg.in 59 D
🛡️ SEO 42 🤖 GEO 82 ⚡ Perf 29 🏗️ Arch 68

mtg.in — Global SEODiff Score 59/100

mtg.in
📊

Among all indexed domains, mtg.in ranks in the top echelon with an ACRI of 87, demonstrating that its content is highly visible to AI systems. Compared to other developer sites (avg score: 58), mtg.in performs above the benchmark, suggesting strong competitive positioning in AI search. Its server-rendered architecture ensures AI crawlers receive complete HTML on first request, a key advantage for extractability. A 6.7× bloat ratio is typical for sites in this tech tier — not wasteful, but streamlining could further boost extractability. Minimal structured data (1 block) limits the site's ability to communicate entity relationships to AI systems. Robots.txt grants unrestricted access to the key AI user-agents, which is the strongest starting position for AI visibility.

59
D — Global SEODiff Score
Comprehensive search visibility assessment
Below average — Performance (29) needs urgent attention.
🎯 Top Fix: Fix title tag length → +3 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 25, 2026 · 📋 API
Does your site score higher than mtg.in?
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)42 × 0.25 = 10.5
🤖 AI Readiness / GEO (40% weight)82 × 0.40 = 32.8
⚡ Performance (20% weight)29 × 0.20 = 5.8
🏗️ Architecture & Trust (15% weight)68 × 0.15 = 10.2
Weighted sum = 10.5 + 32.8 + 5.8 + 10.2
Global SEODiff Score = 59 (D)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
100
Rendering
avg 93
84
Structure
avg 36
42
Schema
avg 9
85
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 36%
Rank #364085
-35 pts
Gap
AI (ACRI)
Top 1%
Score 87/100

mtg.in ranks much higher on Google (Tranco Top 36%) 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 mtg.in ranks here

Tech stackWordPress
Industrydeveloper
RenderingSSR
Schema coverage1 blocks
Token bloat6.7×

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

42/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

90 chars
Too long

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

171 chars
Too long

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✗ Exactly 1 <h1> tag — found 0
  • ✓ Has <h2> headings — found 34
  • ✗ <h2> not before <h1>

🔍 Indexability

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

🌐 Social / OpenGraph

  • ✓ og:title — Best Books for Olympiads, NEET, JEE and CBSE Boards
  • ✓ og:description — MTG Learning Media is a trusted name for creating quality books for the preparation of Olympiads, NEET, JEE Mains & Advanced, BITSAT, and Other Engineering Entrance Exams.
  • ✗ 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

82/100 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 developer sector, hikkoshizamurai.jp (ACRI: 88) 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 →
mtg.in
74
Your ACRI Score
88
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. hikkoshizamurai.jp has schema coverage of 5 blocks and uses Custom / Proprietary. 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 84/100 — Excellent
Structured Elements 1102 elements (1102 lists, 0 rows, 0 headers)
Total Words5157
Raw Density21.4%

🏷️ 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

76
AI Extractability
Medium
Crawl Cost
None
Blocklist Risk
Extractability76/100 — AI models can easily extract answers from this page
Crawl CostMedium (50/100) — moderate for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

14%
🗑️ 86%
Useful Content (69.7 KB)Bloat (394.1 KB)
Token Bloat Ratio6.7× — Normal

Multimodal Readiness

Visual Context10% Optimized for Vision
Image Alt Coverage28 / 278 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Only 10% of images have alt text. Add descriptive alt attributes so multimodal AI (ChatGPT Vision) can understand your images.

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 85.0% · SNR: 0.18 · Signal: 17854 / Noise: 100880 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 mtg.in 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
Educational books, magazines, and eBooks for competitive exams
Target Audience
Students preparing for engineering, medical, and other competitive exams
Pricing Model
Subscription, online purchase, and offline payment options
🔗 Integration Partners
CCaAvenue
🛡️ Compliance Standards
SOC2
Model: mlx-community/Qwen2.5-7B-Instruct-4bit · Analyzed: 2026-02-27 · Data extracted from the site’s main content via strict JSON prompting.

🔧 Tech Stack

FrameworkWordPress
AI-Readiness Score85/100
Servernginx/1.20.0
CDN
HTTP Status200
Load Time1762 ms
Raw HTML Size463.8 KB
Visible Text Size69.7 KB

Performance & Speed

29/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

1762 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

5420
DOM nodes
464 KB
HTML payload
Heavy page — consider reducing DOM complexity

🗄️ Cache & CDN

  • ✗ Cache-Control header
  • ✗ CDN cache status
  • ✗ CDN detected

🔬 Tracker Tax

0
tracker scripts
0
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
📐 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

68/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

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

🔗 Linking

1131
internal links
13
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 74/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for mtg.in
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/mtg.in" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=mtg.in" 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 2 pages · Deep-10

Homepage ACRI
74
Single-page score
-4
Consistent readability
Δ delta
Site-Wide ACRI
70
Avg across 2 pages · Range 56–85
Topical Cohesion
1%
Topical Drift
TF-IDF cosine similarity
Total Words
9272
Avg Bloat
10.8×
Page Type ACRI Token Bloat Words Status
https://mtg.in/faq
FAQ's - MTG Learning Media
pricing 85 9.4× 9050 💰 Pricing
https://mtg.in/blog blog 56 12.2× 222
📂
Health by Sub-Directory
Average ACRI and top issues aggregated by URL path prefix
Path Pages Avg ACRI Ghost % Bloat Top Issue
/faq/ 1 85 0% 9.4× High JS Bloat
/blog/ 1 56 0% 12.2× High JS Bloat
🔄 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/mtg.in

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

🔗 Similar developer Sites

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
mtg.in (this site) 74 87 WordPress 6.7× 1
xn--80aefbvrodbz.xn--p1ai 82 90 WordPress 7.9× 1 Compare →
gillmarine.com 82 84 WordPress 2.9× 1 Compare →
jitterbit.net 82 89 WordPress 2.7× 1 Compare →
fastpng.com 84 90 WordPress 3.9× 2 Compare →
blastengine.jp 82 95 WordPress 2.7× 3 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to mtg.in. 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 Mtg?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Mtg does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Mtg work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Mtg."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for mtg.in:

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