gather.town
Weak AI visibility with 16 of 48 criteria passing. Biggest gap: llms.txt file.
Verdict
Critical AEO gaps at 39/100 - gather.town is largely invisible to AI engines. Key strengths include Fact & Data Density, Canonical URL Strategy, and Content Cannibalization. Priority gaps: llms.txt File, Schema.org Structured Data, 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
Add a machine-readable llms.txt file at your domain root that describes your site, services, and key pages for AI engines.
Create a comprehensive llms-full.txt with detailed page descriptions, content summaries, and topic taxonomy.
Update robots.txt to explicitly allow AI crawlers and include sitemap directive.
Generate a comprehensive sitemap with lastmod dates for all important pages.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow AI crawlers.
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
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.
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.
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.
Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.
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.
Add Organization schema with consistent name, address, phone (NAP). Include sameAs links to social profiles and authoritative directories to strengthen entity recognition.
Place a concise 40-80 word answer block in the first 300 words of each page. Avoid throat-clearing openers like "In this article..." and lead with the answer.
Sections within pages contain identical or near-identical text. LLMs may flag this as low-quality or thin content, reducing citation authority. Rewrite duplicate blocks with unique angles.
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.
Fix It With AI43
Score Breakdown
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