[{"data":1,"prerenderedAt":59},["ShallowReactive",2],{"docs-content:geo-audit":3},{"html":4,"toc":5},"\u003Ch1>geo-audit\u003C/h1>\n\u003Cp>\u003Cstrong>Diagnose why AI can't find, cite, or recommend your website.\u003C/strong>\u003C/p>\n\u003Cp>\u003Ccode>geo-audit\u003C/code> is an open-source Claude Code skill that runs a comprehensive Generative Engine Optimization (GEO) audit. It tells you exactly what's blocking ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews from discovering and citing your content — and gives you a prioritized fix plan.\u003C/p>\n\u003Cp>\u003Cstrong>Repository\u003C/strong>: \u003Ca href=\"https://github.com/Cognitic-Labs/geoskills\">github.com/Cognitic-Labs/geoskills\u003C/a>\u003C/p>\n\u003Ch2 id=\"installation\">Installation\u003C/h2>\n\u003Ch3 id=\"via-skillssh\">Via skills.sh\u003C/h3>\n\u003Cpre>\u003Ccode class=\"language-bash\"># Install geo-audit only\nnpx skills add Cognitic-Labs/geoskills --skill geo-audit\n\n# Or install all geoskills\nnpx skills add Cognitic-Labs/geoskills\n\u003C/code>\u003C/pre>\n\u003Ch3 id=\"via-clawhub\">Via ClawHub\u003C/h3>\n\u003Cpre>\u003Ccode class=\"language-bash\">clawhub install geoskills\n\u003C/code>\u003C/pre>\n\u003Ch3 id=\"manual-install\">Manual Install\u003C/h3>\n\u003Cpre>\u003Ccode class=\"language-bash\">git clone https://github.com/Cognitic-Labs/geoskills.git ~/.claude/skills/geoskills\n\u003C/code>\u003C/pre>\n\u003Ch2 id=\"usage\">Usage\u003C/h2>\n\u003Cp>In Claude Code, run:\u003C/p>\n\u003Cpre>\u003Ccode>/geo-audit https://example.com\n\u003C/code>\u003C/pre>\n\u003Cp>No configuration required. All four analysis agents launch in parallel automatically.\u003C/p>\n\u003Ch3 id=\"aivsrank-integration\">AIvsRank Integration\u003C/h3>\n\u003Cp>AIvsRank API integration is coming soon. All skills work fully without any API key.\u003C/p>\n\u003Ch2 id=\"how-it-works\">How It Works\u003C/h2>\n\u003Cp>geo-audit evaluates your site across four dimensions using a 3-layer model:\u003C/p>\n\u003Cpre>\u003Ccode>+---------------------------------------------+\n|              SIGNAL LAYER (25%)             |\n|         Entity & Brand Signals              |\n|   Wikipedia · LinkedIn · Reddit · Reviews   |\n+---------------------------------------------+\n|             CONTENT LAYER (35%)             |\n|           Content Citability                |\n|  Answer Blocks · Stats · Structure · E-E-A-T|\n+---------------------------------------------+\n|              DATA LAYER (40%)               |\n|   Technical Access (20%) + Schema (20%)     |\n|  AI Crawlers · SSR · llms.txt · JSON-LD     |\n+---------------------------------------------+\n\u003C/code>\u003C/pre>\n\u003Cp>\u003Cstrong>Composite formula\u003C/strong>: \u003Ccode>GEO Score = Technical×0.20 + Citability×0.35 + Schema×0.20 + Brand×0.25\u003C/code>\u003C/p>\n\u003Ch2 id=\"what-gets-analyzed\">What Gets Analyzed\u003C/h2>\n\u003Ch3 id=\"technical-accessibility-20\">Technical Accessibility (20%)\u003C/h3>\n\u003Cul>\n\u003Cli>AI crawler access: GPTBot, ClaudeBot, Google-Extended, PerplexityBot, and 7 more\u003C/li>\n\u003Cli>\u003Ccode>robots.txt\u003C/code> and \u003Ccode>X-Robots-Tag\u003C/code> headers\u003C/li>\n\u003Cli>Server-side rendering (SSR) vs. client-side rendering (CSR)\u003C/li>\n\u003Cli>\u003Ccode>llms.txt\u003C/code> presence and completeness\u003C/li>\n\u003Cli>HTTPS, response time, compression\u003C/li>\n\u003Cli>Sitemap, meta tags, Open Graph, canonical URLs\u003C/li>\n\u003C/ul>\n\u003Ch3 id=\"content-citability-35\">Content Citability (35%)\u003C/h3>\n\u003Cul>\n\u003Cli>Answer block quality (Q&A patterns, definitions, FAQ)\u003C/li>\n\u003Cli>Self-containment (passages understandable in isolation)\u003C/li>\n\u003Cli>Statistical density (numbers, sources, data recency)\u003C/li>\n\u003Cli>Structural clarity (headings, lists, tables, paragraph length)\u003C/li>\n\u003Cli>Expertise signals (author bylines, expert quotes, publication dates)\u003C/li>\n\u003C/ul>\n\u003Ch3 id=\"structured-data-20\">Structured Data (20%)\u003C/h3>\n\u003Cul>\n\u003Cli>Organization / LocalBusiness schema with \u003Ccode>sameAs\u003C/code>\u003C/li>\n\u003Cli>Article / BlogPosting schema with author and dates\u003C/li>\n\u003Cli>Speakable property for AI voice assistants\u003C/li>\n\u003Cli>FAQPage, HowTo, BreadcrumbList schemas\u003C/li>\n\u003Cli>JSON-LD format and syntax validation\u003C/li>\n\u003Cli>Auto-generated fix templates for missing schemas\u003C/li>\n\u003C/ul>\n\u003Ch3 id=\"entity-amp-brand-signals-25\">Entity & Brand Signals (25%)\u003C/h3>\n\u003Cul>\n\u003Cli>Wikipedia / Wikidata entity presence\u003C/li>\n\u003Cli>LinkedIn, Crunchbase, industry directory listings\u003C/li>\n\u003Cli>Reddit discussions, YouTube presence\u003C/li>\n\u003Cli>Cross-source brand name and description consistency\u003C/li>\n\u003C/ul>\n\u003Ch2 id=\"sample-output\">Sample Output\u003C/h2>\n\u003Cpre>\u003Ccode>GEO Audit: example.com\n   Business type: SaaS (detected)\n   Pages to analyze: 8\n\nRunning 4 parallel analyses...\n   Technical Accessibility: 72/100 (3 issues)\n   Content Citability: 58/100 (5 issues)\n   Structured Data: 45/100 (4 issues)\n   Entity & Brand: 81/100 (2 issues)\n\nGEO Score: 62/100 (Grade C: Developing)\n\nFull report: GEO-AUDIT-example-com-2026-03-12.md\n\u003C/code>\u003C/pre>\n\u003Cp>The generated report includes:\u003C/p>\n\u003Cul>\n\u003Cli>Score breakdown with sub-dimensions\u003C/li>\n\u003Cli>Prioritized issue list (Critical to Low)\u003C/li>\n\u003Cli>Specific fix instructions per issue\u003C/li>\n\u003Cli>Ready-to-use JSON-LD templates\u003C/li>\n\u003Cli>Top 5 quick wins with expected point gains\u003C/li>\n\u003Cli>30-day improvement roadmap\u003C/li>\n\u003C/ul>\n\u003Ch2 id=\"score-grades\">Score Grades\u003C/h2>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>Grade\u003C/th>\n\u003Cth>Range\u003C/th>\n\u003Cth>Meaning\u003C/th>\n\u003C/tr>\n\u003C/thead>\n\u003Ctbody>\u003Ctr>\n\u003Ctd>A\u003C/td>\n\u003Ctd>85-100\u003C/td>\n\u003Ctd>AI-optimized. Likely cited by major AI engines.\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>B\u003C/td>\n\u003Ctd>70-84\u003C/td>\n\u003Ctd>Solid foundation. Targeted fixes push to A-tier.\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>C\u003C/td>\n\u003Ctd>50-69\u003C/td>\n\u003Ctd>Significant gaps. Structured 30-day plan needed.\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>D\u003C/td>\n\u003Ctd>30-49\u003C/td>\n\u003Ctd>Major issues. Prioritize critical fixes first.\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>F\u003C/td>\n\u003Ctd>0-29\u003C/td>\n\u003Ctd>Fundamental problems blocking AI discovery.\u003C/td>\n\u003C/tr>\n\u003C/tbody>\u003C/table>\n\u003Ch2 id=\"business-type-adjustments\">Business Type Adjustments\u003C/h2>\n\u003Cp>geo-audit auto-detects your business type and adjusts scoring weights accordingly:\u003C/p>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>Type\u003C/th>\n\u003Cth>Key Adjustments\u003C/th>\n\u003C/tr>\n\u003C/thead>\n\u003Ctbody>\u003Ctr>\n\u003Ctd>SaaS\u003C/td>\n\u003Ctd>Rendering +10%, Answer Blocks +10%, FAQ/HowTo schema +15%\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>E-commerce\u003C/td>\n\u003Ctd>Product schema +20%, Statistical Density +15%, Reviews +15%\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>Publisher\u003C/td>\n\u003Ctd>All citability +10%, Article schema +15%, Entity Recognition +10%\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>Local\u003C/td>\n\u003Ctd>LocalBusiness schema +25%, Directories +20%\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>Agency\u003C/td>\n\u003Ctd>Entity Recognition +15%, Expertise Signals +15%\u003C/td>\n\u003C/tr>\n\u003C/tbody>\u003C/table>\n\u003Ch2 id=\"research-foundation\">Research Foundation\u003C/h2>\n\u003Cp>The scoring methodology synthesizes findings from 101+ sources:\u003C/p>\n\u003Cul>\n\u003Cli>\u003Cstrong>Aggarwal et al. (2023)\u003C/strong> — "GEO: Generative Engine Optimization" (Princeton / Georgia Tech)\u003C/li>\n\u003Cli>\u003Cstrong>BrightEdge (2024-2025)\u003C/strong> — AI citation correlation studies\u003C/li>\n\u003Cli>\u003Cstrong>Google Search Central\u003C/strong> — Schema.org and rich results documentation\u003C/li>\n\u003Cli>\u003Cstrong>SparkToro / Zyppy\u003C/strong> — Zero-click search and AI answer source analysis\u003C/li>\n\u003Cli>Backlinko, Ahrefs, Semrush, Moz, and 90+ industry publications\u003C/li>\n\u003C/ul>\n\u003Ch2 id=\"diagnostic-vs-measurement\">Diagnostic vs. Measurement\u003C/h2>\n\u003Cp>geo-audit identifies \u003Cstrong>what to fix\u003C/strong>. \u003Ca href=\"https://aivsrank.com\">AIvsRank.com\u003C/a> measures \u003Cstrong>how visible you actually are\u003C/strong> across AI platforms over time — tracking real mentions in ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews.\u003C/p>\n\u003Cp>Together, they give you the complete picture.\u003C/p>\n",[6,10,14,17,20,23,26,29,32,35,38,41,44,47,50,53,56],{"id":7,"text":8,"level":9},"installation","Installation",2,{"id":11,"text":12,"level":13},"via-skillssh","Via skills.sh",3,{"id":15,"text":16,"level":13},"via-clawhub","Via ClawHub",{"id":18,"text":19,"level":13},"manual-install","Manual Install",{"id":21,"text":22,"level":9},"usage","Usage",{"id":24,"text":25,"level":13},"aivsrank-integration","AIvsRank Integration",{"id":27,"text":28,"level":9},"how-it-works","How It Works",{"id":30,"text":31,"level":9},"what-gets-analyzed","What Gets Analyzed",{"id":33,"text":34,"level":13},"technical-accessibility-20","Technical Accessibility (20%)",{"id":36,"text":37,"level":13},"content-citability-35","Content Citability (35%)",{"id":39,"text":40,"level":13},"structured-data-20","Structured Data (20%)",{"id":42,"text":43,"level":13},"entity-brand-signals-25","Entity & Brand Signals (25%)",{"id":45,"text":46,"level":9},"sample-output","Sample Output",{"id":48,"text":49,"level":9},"score-grades","Score Grades",{"id":51,"text":52,"level":9},"business-type-adjustments","Business Type Adjustments",{"id":54,"text":55,"level":9},"research-foundation","Research Foundation",{"id":57,"text":58,"level":9},"diagnostic-vs-measurement","Diagnostic vs. Measurement",1780370750430]