dol.gov 71 B
🛡️ SEO 41 🤖 GEO 82 ⚡ Perf 74 🏗️ Arch 86

dol.gov — Global SEODiff Score 71/100

dol.gov
📊

dol.gov achieves a 74/100 on the AI-Crawler Reality Index, reflecting above-average readiness for AI-driven discovery. Within the government vertical, this places dol.gov 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. A tight 3.2× token bloat ratio reflects disciplined markup: minimal noise between the crawler and the content it needs. Zero schema blocks puts this site at a disadvantage in knowledge graph and AI-answer pipelines that rely on explicit structured data. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.

71
B — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Traditional SEO (41) is your bottleneck.
🎯 Top Fix: Add Organization + WebSite JSON-LD → +5–8 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 18, 2026 · 📋 API
📈 ACRI Trend 2 snapshots
Mar 11 Mar 18
🔔 Recent AI Indexing Activity
🔄 Mar 18 Content change detected
Does your site score higher than dol.gov?
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)41 × 0.25 = 10.2
🤖 AI Readiness / GEO (40% weight)82 × 0.40 = 32.8
⚡ Performance (20% weight)74 × 0.20 = 14.8
🏗️ Architecture & Trust (15% weight)86 × 0.15 = 12.9
Weighted sum = 10.2 + 32.8 + 14.8 + 12.9
Global SEODiff Score = 71 (B)
📊 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 0.3%
Rank #3095
+22 pts
Gap
AI (ACRI)
Top 22%
Score 74/100

dol.gov 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 dol.gov ranks here

Tech stackCustom / Proprietary
Industrygovernment
RenderingSSR
Schema coverage0 blocks
Token bloat3.2×

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

41/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

31 chars
Good length

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 1
  • ✓ Has <h2> headings — found 2
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://www.dol.gov
  • ✓ 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 — DOL
  • ✗ 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

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 government sector, gep.com (ACRI: 83) 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 →
dol.gov
62
Your ACRI Score
83
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. gep.com has schema coverage of 3 blocks and uses Drupal. 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 105 elements (105 lists, 0 rows, 0 headers)
Total Words713
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

66
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability66/100 — 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

31%
🗑️ 69%
Useful Content (27.1 KB)Bloat (59.9 KB)
Token Bloat Ratio3.2× — Lean

Multimodal Readiness

Visual Context100% Optimized for Vision
Image Alt Coverage11 / 11 images have alt text

TDM Rights

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

🔥 Structural Entropy Check Research

45 Entropy
Fair Token Bloat: Medium
Noise Ratio: 68.9% · SNR: 0.45 · Signal: 6930 / Noise: 15331 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 dol.gov 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
The Department of Labor's Office of Labor-Management Standards (OLMS) protects union democracy and financial accountability for union members by investigating
Target Audience
Union members, labor organizers, government regulators, and legal professionals involved in labor relations.
Pricing Model
⚠ SEMANTIC VOID
🛡️ Compliance Standards
LMRDA
🏆 Competitive Moat
The OLMS’s investigative authority and enforcement capabilities, combined with its focus on transparency and accountability, create a strong competitive advantage.
📊 Content Depth
6/10
🔄 Programmatic SEO Signals
FAQ schemaForm LM-2 instructionsForm LM-30 instructions
⚡ Key Pain Points
• Union financial mismanagement
• Potential embezzlement and fraud
• Lack of transparency in union finances
• Difficulties in complying with reporting requirements
Analyzed by SEODiff AI · 2026-02-28

🔧 Tech Stack

AI-Readiness Score50/100
Server
CDN
HTTP Status200
Load Time739 ms
Raw HTML Size87.0 KB
Visible Text Size27.1 KB

Performance & Speed

74/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

739 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

743
DOM nodes
87 KB
HTML payload
Lean page — fast for bots and users

🗄️ Cache & CDN

  • ✓ Cache-Control header → public, max-age=60
  • ✗ 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
crazyegg.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

86/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

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

🔗 Linking

114
internal links
28
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 62/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for dol.gov
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/dol.gov" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=dol.gov" 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 1009 pages · Deep-10

Homepage ACRI
62
Single-page score
-7
Moderate hidden bloat
Δ delta
Site-Wide ACRI
56
Avg across 1009 pages · Range 0–87
Topical Cohesion
3%
Topical Drift
TF-IDF cosine similarity
Total Words
1239619
Avg Bloat
58.1×
RAG Fractures [?]
61
⚠️
61 RAG-Chunking Fractures Detected

Poorly formatted tables or pricing grids on 61 pages will be split incorrectly during RAG chunking, causing AI models to hallucinate prices and features.

Page Type ACRI Token Bloat Words Status
https://www.dol.gov/agencies/olms/reports/forms/lm-10/faq
FORM LM-10 - Employer Reports Frequently Asked Questions | U.S. Department of Labor
pricing 87 1.9× 19695 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2020
2020 Annual Report | U.S. Department of Labor
pricing 82 3.5× 6662 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2022
2022 Annual Report | U.S. Department of Labor
pricing 82 3.1× 8278 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2017
2017 Annual Report | U.S. Department of Labor
pricing 82 3.5× 6911 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2021
2021 Annual Report | U.S. Department of Labor
pricing 82 3.2× 7595 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2023
2023 Annual Report | U.S. Department of Labor
pricing 82 3.1× 8420 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2019
2019 Annual Report | U.S. Department of Labor
pricing 82 3.2× 7739 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2006
2006 Annual Report | U.S. Department of Labor
pricing 82 4.3× 4485 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2007
2007 Annual Report | U.S. Department of Labor
pricing 82 3.7× 5535 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2004
2004 Annual Report | U.S. Department of Labor
pricing 82 5.0× 3464 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2024
2024 Annual Report | U.S. Department of Labor
pricing 82 3.4× 7259 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2009
2009 Annual Report | U.S. Department of Labor
pricing 82 4.3× 4852 💰 Pricing
https://www.dol.gov/agencies/sol/about/regions/san-francisco
San Francisco Regional Office | U.S. Department of Labor
pricing 82 4.8× 3960 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2008
2008 Annual Report | U.S. Department of Labor
pricing 82 4.4× 4344 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2010
2010 Annual Report | U.S. Department of Labor
pricing 82 4.3× 4920 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2018
2018 Annual Report | U.S. Department of Labor
pricing 82 3.5× 6825 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2011
2011 Annual Report | U.S. Department of Labor
pricing 82 4.2× 5142 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2012
2012 Annual Report | U.S. Department of Labor
pricing 82 4.2× 5258 💰 Pricing
https://www.dol.gov/agencies/sol/about/leadership
Office Leadership | U.S. Department of Labor
pricing 82 4.8× 3964 💰 Pricing
https://www.dol.gov/agencies/olms/about/annual-reports/2015
2015 Annual Report | U.S. Department of Labor
pricing 82 3.7× 6226 💰 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
/agencies/ 464 70 0% 14.2× High JS Bloat
/general/ 36 70 0% 14.4× High JS Bloat
🔗
Outbound External Citations
0 unique external domains cited across 1009 pages
whitehouse.gov ×998
usa.gov ×998
oig.dol.gov ×998
osc.gov ×993
disasterassistance.gov ×993
youtube.com ×627
instagram.com ×626
facebook.com ×626
🔄 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/dol.gov

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

🔗 Similar government Sites

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
dol.gov (this site) 62 74 Custom / Proprietary 3.2× 0
allinternationalconference.com 78 80 Custom / Proprietary 1.5× 0 Compare →
jcb.com 78 85 Custom / Proprietary 2.3× 1 Compare →
enva.com 80 84 Custom / Proprietary 1.4× 2 Compare →
cbh.com 79 84 Custom / Proprietary 1.6× 3 Compare →
saskatoon.ca 78 81 Drupal 1.5× 0 Compare →
Compare All 5 Similar Sites →

📊 Semantic Share of Voice

How often would an AI cite dol.gov 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

F 15 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.

49
Homepage ACRI
34
Inner Avg ACRI
+15
ACRI Delta
20%
Homepage Ghost
33%
Inner Avg Ghost
74
Drift Score [?]
Worst Inner Pages
26 40% about https://www.dol.gov/agencies/ofccp/about
26 40% blog https://www.dol.gov/agencies/whd/resources
26 40% blog https://www.dol.gov/agencies/brb/resources
🛡️

E-E-A-T Trust Signals

C 45/100

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
Address: 200 Constitution Ave NW, Room N-2420, Washington, DC 20210, Attention: FOIA Request
🔗

Citation Profile

34 DOMAINS

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

178
Total Links
34
Unique Domains
11.9
Avg/Page
19%
Diversity
whitehouse.gov oig.dol.gov disasterassistance.gov usa.gov osc.gov youtube.com twitter.com linkedin.com instagram.com facebook.com
🏘️ Outbound Neighborhood Trust Avg Trust: 49.6

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

🩹

Remediation Patches

COPY-PASTE

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

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for dol.gov:

Current Score
74
Projected Score
87
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
🔍 Found indexing issues?
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