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dalus.io
WINTER 2025

dalus.io

Weak AI visibility with 20 of 48 criteria passing. Biggest gap: llms.txt file.

Developer Tools & InfrastructureDeveloper Platforms
48/100
F
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
6/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
4/10
Technical Foundation
~10% weight
6/10
AI Discovery
~10% weight
3/10

Verdict

Below-average AEO readiness at 48/100 - multiple areas need attention. Key strengths include Content Cannibalization, Duplicate Content Blocks, and Cross-Page Duplicate Content. Priority gaps: llms.txt File, Schema.org Structured Data, and Comprehensive FAQ Section. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

How to Improve

Current
48/100
Projected
79/100
43Total Fixes
16Quick Wins
~89hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersLink orphan pages into site navigationAdd content freshness signalsAdd definition-style contentAdd ai.txt and content licensingIncrease fact and data densityFix canonical URL strategyImprove query-answer alignmentAdd visible date signalsFocus blog content on core expertiseIncrease content depth and structureImprove citation-ready writing qualityAdd answer-first content placementPackage evidence for AI enginesAdd image context for AI engines
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Create complete sitemap.xml
critical|medium
Configure robots.txt for AI crawlers
critical|low
Fix canonical URL strategy
critical|low
Add internationalization signals
critical|medium
Reduce document weight
medium|low
Fix HTML structure and meta tags
low|low
Improve server response efficiency
medium|low
Reduce render-blocking resources
low|low

Top Opportunities10

Ensure blog content consistently covers your core expertise areas rather than scattering across unrelated topics. AI engines build authority models - a site about "Medicare coverage" that also publishes about humidifiers and groceries dilutes its topical authority.

Expand articles to 1000+ words with structured H2/H3 sections, comparison tables, and expert analysis. Thin content (under 300 words) is rarely cited by AI engines. Deep, well-structured articles demonstrate expertise.

Add specific numbers, percentages, statistics, and data points throughout your content. Fact-dense content gives AI engines concrete data to cite rather than vague claims.

Use HTML tables for comparison data and ordered/unordered lists for features, steps, and specifications. Structured data formats are directly extractable by AI engines for answers.

Create a dedicated FAQ page with FAQPage schema markup. Cover common questions about your products, services, and industry to become a direct answer source for AI engines.

Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.

Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.

Define the primary entity in the first 500 characters, use consistent terminology (same term 70%+), and add "unlike X" signals to help AI engines distinguish your topics.

Write 20-25 word self-contained answer sentences immediately after each H2 heading. 72.4% of AI-cited posts use this pattern - it gives engines a ready-made snippet to quote.

Implement JSON-LD structured data (Organization, Service, Product, FAQPage) on key pages. Schema markup helps AI engines extract and cite your content accurately.

Fix It With AI44

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dalus.io/privacyF36
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