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diagon.ai

diagon.ai

Moderate AI visibility with 28 of 48 criteria passing. Biggest gap: comprehensive faq section.

54/100
4 since v1
F
Citation Avg
Answer Readiness
~40% weight
7/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
4/10
Technical Foundation
~10% weight
6/10
AI Discovery
~10% weight
8/10

Verdict

Below-average AEO readiness at 54/100 - multiple areas need attention. Key strengths include llms.txt File, robots.txt for AI Crawlers, and Sitemap Completeness. Priority gaps: Comprehensive FAQ Section, RSS/Atom Feed, and Content Licensing & AI Permissions.

#2809of 13363
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How to Improve

Current
54/100
Projected
80/100
45Total Fixes
14Quick Wins
~98hEst. Effort
Quick Wins
Create /llms.txt fileStrengthen entity authority (NAP)Configure robots.txt for AI crawlersAdd definition-style contentAdd direct answer paragraphsAdd ai.txt and content licensingEnhance author and expert schemaFix canonical URL strategyExtend schema to inner pagesImprove query-answer alignmentAdd visible date signalsMake pages solve the user task fasterReduce extraction frictionReduce document weight
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Fix HTML structure and meta tags
medium|low
Reduce document weight
high|low
Configure robots.txt for AI crawlers
high|trivial
Fix canonical URL strategy
critical|low
Improve server response efficiency
critical|medium
Add internationalization signals
critical|medium
Reduce render-blocking resources
low|low
Create complete sitemap.xml
low|low

Top Opportunities10

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.

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.

Include "our analysis", "our data", "our testing" phrases backed by original research or proprietary data. 52.2% of AI-cited posts contain owned data signals.

Publish original research, statistics, case studies, or proprietary data that AI engines can cite. Unique data points make your content a primary source rather than a derivative one.

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

Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.

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

Include dateModified schema, visible last-updated dates, and time elements on content pages. Fresh content signals help AI engines prioritize your pages over stale alternatives.

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.

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Site Pages

www.diagon.ai/products/product_14ca5ffc-aa20-5263-aaa7-a9...D40
Mazak VORTEX HORIZONTAL PROFILER 160 | 5-Axis Horizontal Machining Center with Tilting Table | Diagon
www.diagon.ai/products/product_dea7c3f0-64e2-5a0f-ac7f-e8...F39
SMTCL CW61160B | Heavy-Duty Engine Lathe | Diagon
Changes since v1Last audited 52 days ago
50
54
+4
View full comparison →
Increase Content DepthAdd Structured Tables & ListsBuild Comprehensive FAQ SectionAdd Owned Data SignalsAdd Original Data & Case StudiesRestructure Content as Q&AAdd Direct Answer ParagraphsImprove Question-Answer AlignmentAdd Content Freshness SignalsAdd Entity Disambiguation

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