mako.cc 59 D
🛡️ SEO 14 🤖 GEO 78 ⚡ Perf 80 🏗️ Arch 55

mako.cc — Global SEODiff Score 59/100

mako.cc
📊

At 67/100, the ACRI for mako.cc indicates strong fundamentals in AI extractability, surpassing the majority of indexed sites. Compared to other education sites (avg score: 58), mako.cc performs above the benchmark, suggesting strong competitive positioning in AI search. Content is delivered server-side, meaning bots and AI agents can parse the full page without executing JavaScript. A tight 2.4× token bloat ratio reflects disciplined markup: minimal noise between the crawler and the content it needs. No structured data was detected, which means AI systems must infer all entities and relationships from raw HTML alone. All major AI bot user-agents (GPTBot, ClaudeBot, CCBot, Google-Extended) are permitted by robots.txt, ensuring broad AI crawler access.

59
D — Global SEODiff Score
Comprehensive search visibility assessment
Below average — Traditional SEO (14) needs urgent attention.
🎯 Top Fix: Add Organization + WebSite JSON-LD → +5–8 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 28, 2026 · 📋 API
📈 ACRI Trend 2 snapshots
Feb 23 Feb 28
🔔 Recent AI Indexing Activity
No recent changes detected by adaptive crawler.
Does your site score higher than mako.cc?
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)14 × 0.25 = 3.5
🤖 AI Readiness / GEO (40% weight)78 × 0.40 = 31.2
⚡ Performance (20% weight)80 × 0.20 = 16.0
🏗️ Architecture & Trust (15% weight)55 × 0.15 = 8.2
Weighted sum = 3.5 + 31.2 + 16.0 + 8.2
Global SEODiff Score = 59 (D)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
36
Structure
avg 36
0
Schema
avg 9
50
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 37%
Rank #366631
Aligned
Gap
AI (ACRI)
Top 41%
Score 67/100

mako.cc has balanced Google and AI visibility — both rank roughly in the same tier. ACRI measures technical crawler readiness. Read the methodology →

Why mako.cc ranks here

Tech stackCustom / Proprietary
Industryeducation
RenderingSSR
Schema coverage0 blocks
Token bloat2.4×

Fastest improvements

  • Add basic Organization and WebSite JSON-LD to fix “0 schema blocks” (see Schema Coverage).
  • 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

14/100 25 % of Global Score 🟡 Medium Confidence

📝 Title Tag

18 chars
Too short

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

0 chars
Missing

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✗ Exactly 1 <h1> tag — found 0
  • ✓ Has <h2> headings — found 4
  • ✗ <h2> not before <h1>

🔍 Indexability

  • ✗ Canonical tag present
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✗ HTML lang attribute
  • ✗ 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

78/100 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, educationdirectory.com.au (ACRI: 86) 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 →
mako.cc
52
Your ACRI Score
86
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. educationdirectory.com.au has schema coverage of 4 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 5%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type SSR

📊 Structure & Information Density Docs

Structure Grade 36/100 — Low
Structured Elements 39 elements (39 lists, 0 rows, 0 headers)
Total Words996
Raw Density3.9%
💡Low structure score (36/100). Your content appears as a wall of text with few structured HTML elements. You have 39 list items, 0 table rows, 0 table headers. Convert features into <ul> lists and data into <table> elements to help AI models extract structured information.

🏷️ Schema Health Docs

Organization Schema ❌ Missing
Product / Service Schema ⚠️ Not Found
Total Schema Blocks0 — No JSON-LD detected

Schema Coverage Map

0/7 schema types detected
❌ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡Organization schema missing. AI models cannot identify your brand entity. Without it, your brand won't appear in Knowledge Panels or be associated with your content.
💡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.
💡BreadcrumbList schema missing. AI cannot understand your site hierarchy or how pages relate to each other.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.
💡WebSite schema missing. Add WebSite + SearchAction so Google can generate a Sitelinks Search Box for your brand in AI results.

📐 AI Efficiency Metrics Docs

56
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability56/100 — AI models can partially extract answers from this page
Crawl CostLow (10/100) — efficient for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

41%
🗑️ 59%
Useful Content (7.2 KB)Bloat (10.3 KB)
Token Bloat Ratio2.4× — Lean

Multimodal Readiness

Visual Context100% Optimized for Vision
Image Alt Coverage16 / 16 images have alt text

TDM Rights

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

🔥 Structural Entropy Check Research

65 Entropy
Fair Token Bloat: Medium
Noise Ratio: 58.8% · SNR: 0.70 · Signal: 1855 / Noise: 2649 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…

🔧 Tech Stack

AI-Readiness Score50/100
ServerApache/2.4.66 (Debian)
CDN
HTTP Status200
Load Time638 ms
Raw HTML Size17.6 KB
Visible Text Size7.2 KB

Performance & Speed

80/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

638 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

220
DOM nodes
18 KB
HTML payload
Lean page — fast for bots and users

🗄️ 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

55/100 15 % of Global Score 🟡 Medium Confidence

🗺️ Sitemap & Robots

  • ✗ Sitemap declared in robots.txt
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

28
internal links
55
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
  • ✓ 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 52/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for mako.cc
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/mako.cc" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=mako.cc" 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
52
Single-page score
+20
Subpages outperform homepage
Δ delta
Site-Wide ACRI
72
Avg across 1 pages · Range 72–72
Total Words
461
Avg Bloat
4.4×
Page Type ACRI Token Bloat Words Status
https://mako.cc/contact
Contact Information :: Benjamin Mako Hill
support 72 4.4× 461
📂
Health by Sub-Directory
Average ACRI and top issues aggregated by URL path prefix
Path Pages Avg ACRI Ghost % Bloat Top Issue
/contact/ 1 72 0% 4.4× Healthy
🔗
Outbound External Citations
0 unique external domains cited across 1 pages
gnupg.org ×1
matrix.to ×1
washington.edu ×1
wiki.communitydata.science ×1
uw.edu ×1
extraordinary.leastsquar.es ×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/mako.cc

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

🔗 Similar education Sites

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
mako.cc (this site) 52 67 Custom / Proprietary 2.4× 0
hackersbook.com 77 80 Custom / Proprietary 1.7× 0 Compare →
phlu.ch 77 77 Custom / Proprietary 2.3× 2 Compare →
dituniversity.edu.in 77 78 Custom / Proprietary 2.1× 2 Compare →
stores.sallybeauty.com 77 86 Custom / Proprietary 3.9× 2 Compare →
student.kent.ac.uk 77 84 Custom / Proprietary 5.0× 4 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

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

Add Organization JSON-LD
High Impact ⏱ 5 min
AI models cannot identify your brand entity without Organization schema. This is the #1 fix for AI visibility.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Mako",
  "url": "https://mako.cc",
  "logo": "https://mako.cc/favicon.ico",
  "sameAs": []
}
</script>
Add WebSite + SearchAction JSON-LD
High Impact ⏱ 5 min
Enables the Sitelinks Search Box in Google and allows AI to understand your site structure.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "Mako",
  "url": "https://mako.cc",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://mako.cc/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
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 Mako?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Mako does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Mako work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Mako."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for mako.cc:

Current Score
67
Projected Score
80
Improvement
+13 pts
Add Organization schema +6 pts
Add WebSite schema +4 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