openlibrary.org 63 C
🛡️ SEO 24 🤖 GEO 81 ⚡ Perf 65 🏗️ Arch 76

openlibrary.org — Global SEODiff Score 63/100

openlibrary.org
📊

openlibrary.org achieves a 74/100 on the AI-Crawler Reality Index, reflecting above-average readiness for AI-driven discovery. Within the infrastructure vertical, this places openlibrary.org above the industry average of 57 —, 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. Token bloat registers at 5.6× — acceptable, but reducing inline scripts and redundant markup could yield measurable gains. No structured data was detected, which means AI systems must infer all entities and relationships from raw HTML alone. Robots.txt grants unrestricted access to the key AI user-agents, which is the strongest starting position for AI visibility.

63
C — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Traditional SEO (24) is your bottleneck.
🎯 Top Fix: Add Organization + WebSite JSON-LD → +5–8 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 15, 2026 · 📋 API
📈 ACRI Trend 2 snapshots
Mar 7 Mar 15
🔔 Recent AI Indexing Activity
🔄 Mar 15 Content change detected
Does your site score higher than openlibrary.org?
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)24 × 0.25 = 6.0
🤖 AI Readiness / GEO (40% weight)81 × 0.40 = 32.4
⚡ Performance (20% weight)65 × 0.20 = 13.0
🏗️ Architecture & Trust (15% weight)76 × 0.15 = 11.4
Weighted sum = 6.0 + 32.4 + 13.0 + 11.4
Global SEODiff Score = 63 (C)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
70
Structure
avg 35
0
Schema
avg 9
50
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 0.6%
Rank #5572
+22 pts
Gap
AI (ACRI)
Top 22%
Score 74/100

openlibrary.org 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 openlibrary.org ranks here

Tech stackCustom / Proprietary
RenderingSSR
Schema coverage0 blocks
Token bloat5.6×

Fastest improvements

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

24/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

38 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

165 chars
Too long

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✗ Exactly 1 <h1> tag — found 0
  • ✓ Has <h2> headings — found 11
  • ✗ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://openlibrary.org/
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en
  • ➖ Hreflang tags — N/A (single language site)
  • ✓ 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

81/100 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 →
openlibrary.org
59
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 99 elements (99 lists, 0 rows, 0 headers)
Total Words673
Raw Density14.7%

🏷️ 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

64
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability64/100 — AI models can partially 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

17%
🗑️ 83%
Useful Content (13.8 KB)Bloat (63.3 KB)
Token Bloat Ratio5.6× — Normal

Multimodal Readiness

Visual Context61% Optimized for Vision
Image Alt Coverage45 / 74 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: 82.1% · SNR: 0.22 · Signal: 3544 / Noise: 16203 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

SEODiff AI analyzed the extracted content of openlibrary.org 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
Open Library provides a collaborative platform for creating a comprehensive, open database of all published books, accessible to everyone.
Target Audience
Librarians, authors, book readers, technologists, and anyone interested in expanding access to knowledge.
Pricing Model
⚠ SEMANTIC VOID
🏆 Competitive Moat
Community-driven, open-source platform for building a global library.
📊 Content Depth
5/10
⚡ Key Pain Points
• Limited user interface for book editing
• Lack of structured data for books beyond basic information
Analyzed by SEODiff AI · 2026-02-28

🔧 Tech Stack

AI-Readiness Score50/100
Servernginx/1.28.2
CDN
HTTP Status200
Load Time628 ms
Raw HTML Size77.1 KB
Visible Text Size13.8 KB

Performance & Speed

65/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

628 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

817
DOM nodes
77 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

76/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://openlibrary.org/static/sitemaps/siteindex.xml.gz
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

166
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
  • ✓ 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 59/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for openlibrary.org
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/openlibrary.org" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=openlibrary.org" 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 217 pages · Deep-10

Homepage ACRI
59
Single-page score
-1
Consistent readability
Δ delta
Site-Wide ACRI
58
Avg across 217 pages · Range 0–77
Topical Cohesion
2%
Topical Drift
TF-IDF cosine similarity
Total Words
92626
Avg Bloat
31.7×
Page Type ACRI Token Bloat Words Status
https://openlibrary.org/authors/OL1143A/Gustave_Le_Bon
Gustave Le Bon | Open Library
pricing 77 19.2× 1516 💰 Pricing
https://openlibrary.org/authors/OL117A/Максим_Горький
Максим Горький | Open Library
pricing 77 18.3× 1982 💰 Pricing
https://openlibrary.org/authors/OL1083A/Gurudatta
Gurudatta | Open Library
pricing 72 27.2× 944 💰 Pricing
https://openlibrary.org/authors/OL1129A/Majumdar_R._C.
Ramesh Chandra Majumdar | Open Library
pricing 72 23.1× 1230 💰 Pricing
https://openlibrary.org/authors/OL1123A/Dilip_Kumar_Roy
Dilip Kumar Roy | Open Library
pricing 72 23.6× 1139 💰 Pricing
https://openlibrary.org/authors/OL1124A/Buddha_Prakash
Buddha Prakash | Open Library
pricing 72 25.5× 939 💰 Pricing
https://openlibrary.org/authors/OL1080A/Āla_Māhamuda
Āla Māhamuda | Open Library
pricing 72 27.1× 928 💰 Pricing
https://openlibrary.org/authors/OL1081A/Gulābadāsa_Brokara
Gulābadāsa Brokara | Open Library
pricing 72 26.9× 945 💰 Pricing
https://openlibrary.org/authors/OL1071A/Dīkshita_Ma._Śrī.
Dīkshita, Ma. Śrī. | Open Library
pricing 72 27.7× 584 💰 Pricing
https://openlibrary.org/authors/OL1104A/Vladimir_Il’ich_Lenin
Vladimir Il’ich Lenin | Open Library
pricing 72 20.8× 1827 💰 Pricing
https://openlibrary.org/authors/OL1119A/Gordon_Cullen
Gordon Cullen | Open Library
pricing 72 24.7× 704 💰 Pricing
https://openlibrary.org/authors/OL1033A/Amritlal_B._Shah
Amritlal B. Shah | Open Library
pricing 72 24.3× 1059 💰 Pricing
https://openlibrary.org/authors/OL110A/Mannaraswamighala_Sreeranga_Rajan
Mannaraswamighala Sreeranga Rajan | Open Library
pricing 72 24.7× 1095 💰 Pricing
https://openlibrary.org/authors/OL1013A/Kaṇāda.
Kaṇāda. | Open Library
pricing 72 30.2× 544 💰 Pricing
https://openlibrary.org/authors/OL1180A/Bhāṭī_Deśarājasiṃha
Bhāṭī, Deśarājasiṃha | Open Library
pricing 72 26.4× 974 💰 Pricing
https://openlibrary.org/authors/OL1084A/Dinakara_Joshī
Dinakara Joshī | Open Library
pricing 72 27.0× 937 💰 Pricing
https://openlibrary.org/authors/OL1085A/Kailash_Vajpeyi
Kailash Vajpeyi | Open Library
pricing 72 28.2× 764 💰 Pricing
https://openlibrary.org/authors/OL1006A/Gurdial_Singh
Gurdial Singh | Open Library
pricing 72 26.5× 980 💰 Pricing
https://openlibrary.org/authors/OL1007A/Sant_Singh_Sekhon
Sant Singh Sekhon | Open Library
pricing 72 24.7× 1096 💰 Pricing
https://openlibrary.org/authors/OL1008A/Bhāgīrathi_Nepāka
Bhāgīrathi Nepāka | Open Library
pricing 72 27.0× 946 💰 Pricing
Showing 20 of 100 pages. Unlock full subpage table →
📂
Health by Sub-Directory
Average ACRI and top issues aggregated by URL path prefix
Path Pages Avg ACRI Ghost % Bloat Top Issue
/authors/ 201 62 0% 33.6× High JS Bloat
/products/ 1 0 0% 0.0× Low AI Readiness
/integrations/ 1 0 0% 0.0× Low AI Readiness
/api/ 1 0 0% 0.0× Low AI Readiness
/solutions/ 1 0 0% 0.0× Low AI Readiness
/faq/ 1 0 0% 0.0× Low AI Readiness
/blog/ 1 0 0% 0.0× Low AI Readiness
/terms/ 1 0 0% 0.0× Low AI Readiness
/features/ 1 0 0% 0.0× Low AI Readiness
/careers/ 1 0 0% 0.0× Low AI Readiness
/docs/ 1 39 0% 61.3× High JS Bloat
/help/ 1 52 0% 23.8× High JS Bloat
/pricing/ 1 0 0% 0.0× Low AI Readiness
/privacy/ 1 0 0% 0.0× Low AI Readiness
/case-studies/ 1 0 0% 0.0× Low AI Readiness
🔗
Outbound External Citations
0 unique external domains cited across 217 pages
archive.org ×205
twitter.com ×205
blog.openlibrary.org ×205
bsky.app ×205
github.com ×205
isni.org ×25
id.loc.gov ×25
en.wikipedia.org ×25
🔄 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/openlibrary.org

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

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📊 Semantic Share of Voice

How often would an AI cite openlibrary.org when users ask about topics in this domain's niche? We run entity queries through our 188k-page search index and measure citation probability.

Analyzing citation landscape…

🎭

Bait & Switch Delta

B 4 PAGES

Compares your homepage rendering quality with inner pages. A high drift score means AI crawlers see a polished homepage but degraded inner content — the "bait & switch" that erodes trust.

57
Homepage ACRI
43
Inner Avg ACRI
+14
ACRI Delta
0%
Homepage Ghost
13%
Inner Avg Ghost
16
Drift Score [?]
Worst Inner Pages
39 20% pricing https://openlibrary.org/docs
39 20% pricing https://openlibrary.org/contact
52 0% pricing https://openlibrary.org/help
🛡️

E-E-A-T Trust Signals

C 40/100

Trust indicators extracted from surface pages. These signals help AI systems verify your site's Experience, Expertise, Authoritativeness, and Trustworthiness.

Physical Address
Phone Number
Email Contact
About Page
Contact Page
Privacy Policy
Terms of Service
Named Leadership
🔗

Citation Profile

6 DOMAINS

Outbound citation patterns across surface-crawled pages. Sites that cite diverse, authoritative sources signal higher E-E-A-T to AI systems.

21
Total Links
6
Unique Domains
5.3
Avg/Page
29%
Diversity
blog.openlibrary.org github.com bsky.app twitter.com archive.org library.ca.gov
🏘️ Outbound Neighborhood Trust Avg Trust: 26.1

AI trust scores for the domains openlibrary.org links to. Citing high-trust sources lifts your own credibility signal.

🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to openlibrary.org. 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": "Openlibrary",
  "url": "https://openlibrary.org",
  "logo": "https://openlibrary.org/static/images/openlibrary-128x128.png",
  "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": "Openlibrary",
  "url": "https://openlibrary.org",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://openlibrary.org/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 Openlibrary?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Openlibrary does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Openlibrary work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Openlibrary."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for openlibrary.org:

Current Score
74
Projected Score
90
Improvement
+16 pts
Add Organization schema +6 pts
Add WebSite schema +4 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
🔍 Found indexing issues?
Run a free deep audit to diagnose crawled-not-indexed, soft 404s, redirect errors, and more.
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