copilot.app 68 C
🛡️ SEO 67 🤖 GEO 67 ⚡ Perf 47 🏗️ Arch 100

copilot.app — Global SEODiff Score 68/100

copilot.app
📊

At 82/100, the ACRI for copilot.app indicates strong fundamentals in AI extractability, surpassing the majority of indexed sites. In the infrastructure sector, copilot.app outperforms the average (57), 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. Heavy markup overhead (38.8× bloat) forces AI systems to wade through excess code before finding useful information. Structured data coverage is solid at 2 blocks, covering core entities — expanding to include FAQ or Breadcrumb schemas could strengthen the profile further. All major AI bot user-agents (GPTBot, ClaudeBot, CCBot, Google-Extended) are permitted by robots.txt, ensuring broad AI crawler access.

68
C — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Performance (47) is your bottleneck.
🎯 Top Fix: Reduce token bloat (39×) → +5–10 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 26, 2026 · 📋 API
Does your site score higher than copilot.app?
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)67 × 0.25 = 16.8
🤖 AI Readiness / GEO (40% weight)67 × 0.40 = 26.8
⚡ Performance (20% weight)47 × 0.20 = 9.4
🏗️ Architecture & Trust (15% weight)100 × 0.15 = 15.0
Weighted sum = 16.8 + 26.8 + 9.4 + 15.0
Global SEODiff Score = 68 (C)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
70
Structure
avg 35
44
Schema
avg 10
70
Tech Stack
avg 64
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 23%
Rank #228638
-18 pts
Gap
AI (ACRI)
Top 4%
Score 82/100

copilot.app ranks much higher on Google (Tranco Top 23%) than in AI search (Top 4%). This is the 'Invisible Giant' pattern — implement the patches above to close the AI gap. ACRI measures technical crawler readiness. Read the methodology →

Why copilot.app ranks here

Tech stackNext.js
RenderingSSR
Schema coverage2 blocks
Token bloat38.8×

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

67/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

44 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

151 chars
Good length

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 5
  • ✓ <h2> not before <h1>

🔍 Indexability

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

🌐 Social / OpenGraph

  • ✗ og:title
  • ✗ og:description
  • ✓ 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

67/100 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 infrastructure sector, safely.co.jp (ACRI: 90) 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 →
copilot.app
61
Your ACRI Score
90
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. safely.co.jp has schema coverage of 3 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 5%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type SSR

📊 Structure & Information Density Docs

Structure Grade 70/100 — Good
Structured Elements 104 elements (104 lists, 0 rows, 0 headers)
Total Words716
Raw Density14.5%

🏷️ Schema Health Docs

Organization Schema ✅ Present
Product / Service Schema ⚠️ Not Found
Total Schema Blocks2 block(s) — Basic (low value for AI)

Schema Coverage Map

2/7 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.
💡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.

📐 AI Efficiency Metrics Docs

59
AI Extractability
Medium
Crawl Cost
None
Blocklist Risk
Extractability59/100 — AI models can partially extract answers from this page
Crawl CostMedium (45/100) — moderate for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

2%
🗑️ 98%
Useful Content (4.9 KB)Bloat (186.2 KB)
Token Bloat Ratio38.8× — Bloated

Multimodal Readiness

Visual Context100% Optimized for Vision
Image Alt Coverage43 / 43 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Your HTML is 191.1 KB, but only 4.9 KB is text. 2% useful / 98% bloat. AI crawlers have limited context windows (e.g. 128k tokens). This level of bloat (38.8×) risks context-window truncation by ChatGPT, Claude, and Gemini. Reduce inline scripts, CSS, hydration payloads, and tracking code.

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 97.4% · SNR: 0.03 · Signal: 1260 / Noise: 47662 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

FrameworkNext.js
AI-Readiness Score70/100
ServerVercel
CDNvercel
HTTP Status200
Load Time1164 ms
Raw HTML Size191.1 KB
Visible Text Size4.9 KB

Performance & Speed

47/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

1164 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

892
DOM nodes
191 KB
HTML payload
Moderate weight — acceptable for most scenarios

🗄️ Cache & CDN

  • ✓ Cache-Control header → private, no-cache, no-store, max-age=0, must-revalidate
  • ✗ CDN cache status
  • ✓ CDN detected → vercel

🔬 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

100/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://assembly.com/sitemap.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

152
internal links
29
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
  • ✓ 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 61/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for copilot.app
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/copilot.app" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=copilot.app" 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 infrastructure Sites

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
copilot.app (this site) 61 82 Next.js 38.8× 2
assembly.com 61 82 Next.js 38.8× 2 Compare →
implix.com 61 82 Next.js 38.0× 2 Compare →
getresponse.com 61 82 Next.js 38.0× 2 Compare →
sunweb.de 61 88 Next.js 37.7× 2 Compare →
activefitnessstore.com 60 80 Next.js 39.4× 2 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

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

Reduce Token Bloat
Medium Impact ⏱ 1–2 hrs
Only 2% of your HTML is useful content. AI crawlers waste context window tokens on bloat.
html
<!-- 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>
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 Copilot?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Copilot does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Copilot work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Copilot."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for copilot.app:

Current Score
82
Projected Score
90
Improvement
+8 pts
Reduce token bloat +5 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