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shinkei.systems
WINTER 2022

shinkei.systems

Weak AI visibility with 23 of 48 criteria passing. Biggest gap: llms.txt file.

Developer Tools & InfrastructureDeveloper Platforms
47/100
1 since v1
F
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
6/10
Content Structure
~25% weight
4/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
4/10
AI Discovery
~10% weight
5/10

Verdict

Below-average AEO readiness at 47/100 - multiple areas need attention. Key strengths include Canonical URL Strategy, Content Cannibalization, and Duplicate Content Blocks. Priority gaps: llms.txt File, Q&A Content Format, and RSS/Atom Feed. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

How to Improve

Current
47/100
Projected
79/100
40Total Fixes
11Quick Wins
~82hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersAdd direct answer paragraphsAdd ai.txt and content licensingEnhance author and expert schemaExtend schema to inner pagesAdd visible date signalsIncrease content depth and structureMake 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
Configure robots.txt for AI crawlers
high|trivial
Reduce document weight
high|low
Add internationalization signals
critical|medium
Create complete sitemap.xml
low|low
Improve server response efficiency
medium|low
Reduce render-blocking resources
medium|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 question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.

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.

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.

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

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.

Add Organization schema with consistent name, address, phone (NAP). Include sameAs links to social profiles and authoritative directories to strengthen entity recognition.

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.

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.

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Site Pages

shinkei.systems/technologyF35
Technology | Shinkei Systems
Changes since v1Last audited 85 days ago
48
47
-1
View full comparison →
Focus Content on Core TopicsIncrease Content DepthRestructure Content as Q&AAdd Original Data & Case StudiesAdd Structured Tables & ListsAdd Direct Answer ParagraphsAdd Owned Data SignalsStrengthen Entity Authority (NAP)Add Answer Capsule PatternsIncrease Fact & Data Density

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