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Both targets fall in the Foundation band, indicating significant room for improvement before AI engines will reliably cite or surface this project.
✅ Top Strengths
README robots.txt — Scores 15/100 (highest in the README audit), indicating some allowance for AI crawlers is already in place.
README llms.txt — Score 14/100; an llms.txt file exists for the README target, giving AI systems a structured signal.
README meta tags — Score 11/100; basic Open Graph / meta-description coverage is present.
README content — Score 12/100; content is not thin and includes author signals.
Docs site meta tags — Score 14/100; the docs site has reasonable meta tag coverage relative to other categories.
🚨 Critical Gaps
AI Discovery files missing on both targets (0/100) — Neither /.well-known/ai.txt, /ai/summary.json, /ai/faq.json, nor /ai/service.json exist. These are the primary signals AI engines use to discover and describe a service.
Docs site has no robots.txt or llms.txt (0/100 each) — AI crawlers like GPTBot, ClaudeBot, and PerplexityBot have no explicit permission or guidance for github.github.com/gh-aw/.
Schema/JSON-LD completely absent from the README (0/100) — No WebSite, Organization, or FAQPage structured data is present, preventing Knowledge Graph disambiguation.
Docs site Schema/JSON-LD is minimal (13/100) — The docs site lacks Organization, FAQPage, and VideoObject schema despite having video content.
Brand & Entity signals are very weak — README scores 3/100 and docs site 7/100. No sameAs links to Wikipedia, Wikidata, LinkedIn, or Crunchbase exist to establish entity identity.
🔧 Recommended Fixes
Ordered by estimated impact:
Add AI Discovery files — Create /.well-known/ai.txt, /ai/summary.json, /ai/faq.json, and /ai/service.json on the docs site. This addresses the 0/100 ai_discovery score and is the highest-leverage structural change.
Add robots.txt with AI-bot Allow rules to the docs site — Include explicit Allow for GPTBot, ClaudeBot, and PerplexityBot. Currently 0/100.
Add llms.txt to the docs site — Run geo llms --base-url https://github.github.com/gh-aw to generate a structured content map for AI indexing. Currently 0/100.
Add JSON-LD schema to the README/repo homepage — Add WebSite, Organization (with sameAs links), and FAQPage structured data. This is the single largest gap (0/100) for the README.
Fix negative signals — The README has 9 broken links and keyword stuffing (github at 2.6% density). The docs site has display:none hidden content that AI crawlers may penalize.
Add <link rel="canonical"> to the docs site — Prevents duplicate-content penalties in AI indexing.
Front-load key information — Move the most important content about gh aw into the first 30% of both the README and docs site pages for better AI snippet selection.
Add VideoObject schema — Video content on the docs site has no structured metadata; add name, description, thumbnailUrl, and uploadDate.
📋 Full Score Breakdown by Category
Docs Site (github.github.com/gh-aw/) — Score: 44/100
Category
Score
Robots.txt
0/100
llms.txt
0/100
AI Discovery
0/100
Signals
6/100
Content
7/100
Brand & Entity
7/100
Schema JSON-LD
13/100
Meta Tags
14/100
Negative penalty
-3
Negative signals detected: keyword stuffing (github at 2.8%), hidden text (display:none/visibility:hidden).
All pages cluster in the Foundation band (36–44). Site-wide structural fixes (robots.txt, llms.txt, AI discovery files, JSON-LD schema) will lift all pages simultaneously.
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GEO Audit Report — github/gh-aw
Audit Date: 2026-07-26
Run: §30210865953
📊 Scores
github.github.com/gh-aw/)github.com/github/gh-aw)Both targets fall in the Foundation band, indicating significant room for improvement before AI engines will reliably cite or surface this project.
✅ Top Strengths
llms.txtfile exists for the README target, giving AI systems a structured signal.🚨 Critical Gaps
/.well-known/ai.txt,/ai/summary.json,/ai/faq.json, nor/ai/service.jsonexist. These are the primary signals AI engines use to discover and describe a service.github.github.com/gh-aw/.WebSite,Organization, orFAQPagestructured data is present, preventing Knowledge Graph disambiguation.Organization,FAQPage, andVideoObjectschema despite having video content.sameAslinks to Wikipedia, Wikidata, LinkedIn, or Crunchbase exist to establish entity identity.🔧 Recommended Fixes
Ordered by estimated impact:
/.well-known/ai.txt,/ai/summary.json,/ai/faq.json, and/ai/service.jsonon the docs site. This addresses the 0/100 ai_discovery score and is the highest-leverage structural change.robots.txtwith AI-bot Allow rules to the docs site — Include explicitAllowforGPTBot,ClaudeBot, andPerplexityBot. Currently 0/100.llms.txtto the docs site — Rungeo llms --base-url https://github.github.com/gh-awto generate a structured content map for AI indexing. Currently 0/100.WebSite,Organization(withsameAslinks), andFAQPagestructured data. This is the single largest gap (0/100) for the README.githubat 2.6% density). The docs site hasdisplay:nonehidden content that AI crawlers may penalize.<link rel="canonical">to the docs site — Prevents duplicate-content penalties in AI indexing.gh awinto the first 30% of both the README and docs site pages for better AI snippet selection.VideoObjectschema — Video content on the docs site has no structured metadata; addname,description,thumbnailUrl, anduploadDate.📋 Full Score Breakdown by Category
Docs Site (
github.github.com/gh-aw/) — Score: 44/100Negative signals detected: keyword stuffing (
githubat 2.8%), hidden text (display:none/visibility:hidden).README (
github.com/github/gh-aw) — Score: 55/100Negative signals detected: 9 broken links, keyword stuffing (
githubat 2.6%), popup/modal signals.📄 Sitemap Page Scores
Top pages from the sitemap audit (20 pages crawled):
github.github.com/gh-aw.../blog/2026-01-13-meet-the-workflows-continuous-improvement.../blog/2026-01-13-meet-the-workflows-continuous-refactoring.../blog/2026-01-12-welcome-to-pelis-agent-factory.../blog/2026-01-13-meet-the-workflows-advanced-analytics.../blog/2026-01-13-meet-the-workflows-campaigns.../blog/2026-01-13-meet-the-workflows-continuous-simplicity.../blog/2026-01-13-meet-the-workflows-continuous-style.../agent-factory-status.../blogAll pages cluster in the Foundation band (36–44). Site-wide structural fixes (robots.txt, llms.txt, AI discovery files, JSON-LD schema) will lift all pages simultaneously.
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