/geo-citability
AI citability scoring and optimization. Analyzes web page content to determine how likely AI systems (ChatGPT, Claude, Perplexity, Gemini) are to cite or quote passages from the page. Provides a citability score (0-100) with specific rewrite suggestions.
$ npx -y skills add zubair-trabzada/geo-seo-claude --skill geo-citability --agent claude-codeHow it fires
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/geo-citability
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The summary Claude sees to decide when to auto-load this skill.
AI citability scoring and optimization. Analyzes web page content to determine how likely AI systems (ChatGPT, Claude, Perplexity, Gemini) are to cite or quote passages from the page. Provides a citability score (0-100) with specific rewrite suggestions.
SKILL.md
geo-citability.SKILL.mdname: geo-citability
description: AI citability scoring and optimization. Analyzes web page content to determine how likely AI systems (ChatGPT, Claude, Perplexity, Gemini) are to cite or quote passages from the page. Provides a citability score (0-100) with specific rewrite suggestions.
allowed-tools:
- Read
- Grep
- Glob
- Bash
- WebFetch
- Write
AI Citability Scoring Skill
Core Insight
AI language models cite passages that meet specific structural criteria. Research from Princeton, Georgia Tech, and IIT Delhi (2024) found that GEO-optimized content achieves 30-115% higher visibility in AI-generated responses. The key finding: AI systems preferentially extract and cite passages that are **134-167 words long**, **self-contained** (understandable without surrounding context), **fact-rich** (containing specific statistics, dates, or named entities), and **directly answer a question** in the first 1-2 sentences.
This is fundamentally different from traditional SEO copywriting, which optimizes for keyword density and user engagement metrics. GEO citability optimizes for **extractability** -- the ease with which an AI system can pull a passage from your content and present it as a direct answer.
---
Citability Scoring Rubric (0-100)
Category 1: Answer Block Quality (30% of total score)
This measures whether content contains clear, quotable answer passages that AI systems can extract verbatim.
**Scoring Criteria:**
| Score | Criteria | |---|---| | **90-100** | Every major section opens with a 1-2 sentence direct answer. Uses "X is..." or "X refers to..." patterns. First 40-60 words of each section can stand alone as a complete answer. | | **70-89** | Most sections have clear answer openings. Some definition patterns present. Answers are identifiable but may need minor context. | | **50-69** | Some sections have answer-like openings but many bury the answer in the middle or end of paragraphs. Few explicit definition patterns. | | **30-49** | Answers are generally buried in long paragraphs. No consistent definition patterns. Content is narrative-driven rather than answer-driven. | | **0-29** | No identifiable answer blocks. Content is entirely narrative, conversational, or fragmented. AI would struggle to extract any quotable passage. |
**What to look for:**
- **Definition patterns:** "X is [definition]." / "X refers to [explanation]." / "X means [meaning]."
- **Answer-first structure:** The answer appears in the first sentence, followed by supporting detail.
- **Quantified answers:** "The average cost of X is $Y" rather than "Many factors affect the cost of X."
- **Comparison answers:** "X differs from Y in three ways: [list]" rather than "X and Y are often confused."
**High-citability example:**
Content delivery networks (CDNs) are distributed server systems that cache and serve
web content from locations geographically close to end users. A CDN reduces latency
by 50-70% on average by serving assets from edge servers rather than a single origin
server. The three largest CDN providers as of 2025 are Cloudflare (serving approximately
20% of all websites), Amazon CloudFront, and Akamai Technologies.
Word count: 58. Self-contained: Yes. Facts: 3 specific data points. Definition pattern: Yes.
**Low-citability example:**
If you've ever wondered why some websites load faster than others, the answer might
surprise you. There's this amazing technology that has been around for a while now.
It's changed the way we think about web performance. Let me explain how it works and
why you should care about it for your business.
Word count: 52. Self-contained: No (no topic identified). Facts: 0. Definition pattern: No.
---
Category 2: Passage Self-Containment (25% of total score)
This measures whether individual passages can be extracted and understood without needing the surrounding content.
**Scoring Criteria:**
| Score | Criteria | |---|---| | **90-100** | 80%+ of content blocks are fully self-contained. Each passage names its subject explicitly. No reliance on pronouns referencing earlier content. Contains specific facts within the passage. | | **70-89** | 60-79% of content blocks are self-contained. Most passages name their subject. Occasional pronoun references that require context. | | **50-69** | 40-59% of content blocks are self-contained. Mixed use of explicit subjects and pronouns. Some passages require reading prior sections. | | **30-49** | 20-39% of content blocks are self-contained. Heavy reliance on pronouns and contextual references. Most passages need surrounding text. | | **0-29** | Under 20% self-contained. Content reads as a continuous narrative where extracting any paragraph loses meaning. |
**Self-containment checklist for each passage:**
1. Does the passage explicitly name the subject (not "it," "this," "they")? 2. Can someone understand the main point reading ONLY this passage? 3. Does the passage contain at least one specific fact, statistic, or named entity? 4. Is the passage between 50-200 words (the optimal extraction length)? 5. Does the passage avoid starting with conjunctions ("But," "However," "And") that imply prior context?
---
Category 3: Structural Readability (20% of total score)
This measures the structural formatting that helps AI systems parse and segment content.
**Scoring Criteria:**
| Score | Criteria | |---|---| | **90-100** | Clean H1 > H2 > H3 hierarchy. Question-based headings for informational content. Short paragraphs (2-4 sentences). Tables for comparisons. Ordered lists for processes. Unordered lists for features/options. | | **70-89** | Good heading hierarchy with minor skips. Some question-based headings. Mostly short paragraphs. Some use of tables and lists. | | **50-69** | Heading hierarchy present but inconsistent. Few question-based headings. Mix of short and long paragraphs. Limited tables/lists. | | **30-49** | Minimal heading structure. No question-based headings. Long p
Read more
name: geo-citability description: AI citability scoring and optimization. Analyzes web page content to determine how likely AI systems (ChatGPT, Claude, Perplexity, Gemini) are to cite or quote passages from the page. Provides a citability score (0-100) with specific rewrite suggestions. allowed-tools: - Read - Grep - Glob - Bash - WebFetch - Write
AI Citability Scoring Skill
Core Insight
AI language models cite passages that meet specific structural criteria. Research from Princeton, Georgia Tech, and IIT Delhi (2024) found that GEO-optimized content achieves 30-115% higher visibility in AI-generated responses. The key finding: AI systems preferentially extract and cite passages that are **134-167 words long**, **self-contained** (understandable without surrounding context), **fact-rich** (containing specific statistics, dates, or named entities), and **directly answer a question** in the first 1-2 sentences.
This is fundamentally different from traditional SEO copywriting, which optimizes for keyword density and user engagement metrics. GEO citability optimizes for **extractability** -- the ease with which an AI system can pull a passage from your content and present it as a direct answer.
---
Citability Scoring Rubric (0-100)
Category 1: Answer Block Quality (30% of total score)
This measures whether content contains clear, quotable answer passages that AI systems can extract verbatim.
**Scoring Criteria:**
| Score | Criteria | |---|---| | **90-100** | Every major section opens with a 1-2 sentence direct answer. Uses "X is..." or "X refers to..." patterns. First 40-60 words of each section can stand alone as a complete answer. | | **70-89** | Most sections have clear answer openings. Some definition patterns present. Answers are identifiable but may need minor context. | | **50-69** | Some sections have answer-like openings but many bury the answer in the middle or end of paragraphs. Few explicit definition patterns. | | **30-49** | Answers are generally buried in long paragraphs. No consistent definition patterns. Content is narrative-driven rather than answer-driven. | | **0-29** | No identifiable answer blocks. Content is entirely narrative, conversational, or fragmented. AI would struggle to extract any quotable passage. |
**What to look for:**
- **Definition patterns:** "X is [definition]." / "X refers to [explanation]." / "X means [meaning]."
- **Answer-first structure:** The answer appears in the first sentence, followed by supporting detail.
- **Quantified answers:** "The average cost of X is $Y" rather than "Many factors affect the cost of X."
- **Comparison answers:** "X differs from Y in three ways: [list]" rather than "X and Y are often confused."
**High-citability example:**
Content delivery networks (CDNs) are distributed server systems that cache and serve web content from locations geographically close to end users. A CDN reduces latency by 50-70% on average by serving assets from edge servers rather than a single origin server. The three largest CDN providers as of 2025 are Cloudflare (serving approximately 20% of all websites), Amazon CloudFront, and Akamai Technologies.
Word count: 58. Self-contained: Yes. Facts: 3 specific data points. Definition pattern: Yes.
**Low-citability example:**
If you've ever wondered why some websites load faster than others, the answer might surprise you. There's this amazing technology that has been around for a while now. It's changed the way we think about web performance. Let me explain how it works and why you should care about it for your business.
Word count: 52. Self-contained: No (no topic identified). Facts: 0. Definition pattern: No.
---
Category 2: Passage Self-Containment (25% of total score)
This measures whether individual passages can be extracted and understood without needing the surrounding content.
**Scoring Criteria:**
| Score | Criteria | |---|---| | **90-100** | 80%+ of content blocks are fully self-contained. Each passage names its subject explicitly. No reliance on pronouns referencing earlier content. Contains specific facts within the passage. | | **70-89** | 60-79% of content blocks are self-contained. Most passages name their subject. Occasional pronoun references that require context. | | **50-69** | 40-59% of content blocks are self-contained. Mixed use of explicit subjects and pronouns. Some passages require reading prior sections. | | **30-49** | 20-39% of content blocks are self-contained. Heavy reliance on pronouns and contextual references. Most passages need surrounding text. | | **0-29** | Under 20% self-contained. Content reads as a continuous narrative where extracting any paragraph loses meaning. |
**Self-containment checklist for each passage:**
1. Does the passage explicitly name the subject (not "it," "this," "they")? 2. Can someone understand the main point reading ONLY this passage? 3. Does the passage contain at least one specific fact, statistic, or named entity? 4. Is the passage between 50-200 words (the optimal extraction length)? 5. Does the passage avoid starting with conjunctions ("But," "However," "And") that imply prior context?
---
Category 3: Structural Readability (20% of total score)
This measures the structural formatting that helps AI systems parse and segment content.
**Scoring Criteria:**
| Score | Criteria | |---|---| | **90-100** | Clean H1 > H2 > H3 hierarchy. Question-based headings for informational content. Short paragraphs (2-4 sentences). Tables for comparisons. Ordered lists for processes. Unordered lists for features/options. | | **70-89** | Good heading hierarchy with minor skips. Some question-based headings. Mostly short paragraphs. Some use of tables and lists. | | **50-69** | Heading hierarchy present but inconsistent. Few question-based headings. Mix of short and long paragraphs. Limited tables/lists. | | **30-49** | Minimal heading structure. No question-based headings. Long p
GEO-first SEO skill for Claude Code. Comprehensive AI search optimization for any website — citability scoring, AI crawler analysis, brand authority, schema markup, platform-specific optimization, and PDF reports. If you want learn how to sell this to real businesses, check out the skool community
Repo: zubair-trabzada/geo-seo-claude
Other skills on geo-seo-claude.
- /geo-audit
Full website GEO+SEO audit with parallel subagent delegation. Orchestrates a comprehensive Generative Engine Optimization audit across AI citability, platform analysis, technical infrastructure, content quality, and schema markup. Produces a composite GEO Score (0-100) with
Open skill - /geo-brand-mentions
Brand mention and authority scanner for AI visibility. Analyzes brand presence across platforms that AI models rely on for entity recognition and citation decisions. Produces a Brand Authority Score (0-100) with platform-specific recommendations.
Open skill - /geo-compare
Monthly delta tracking and progress reporting for GEO clients. Compares two GEO audits (baseline vs. current), calculates score improvements across all categories, tracks action item completion, and generates a "here's your progress" client report. Use when user says "compare",
Open skill - /geo-content
Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure
Open skill - /geo-crawlers
AI crawler access analysis. Checks robots.txt, meta tags, and HTTP headers to determine which AI crawlers can access the site. Provides a complete access map and recommendations for maximizing AI visibility while maintaining appropriate control.
Open skill - /geo-llmstxt
Analyzes and generates llms.txt files -- the emerging standard for helping AI systems understand website structure and content. Can validate existing llms.txt files or generate new ones from scratch by crawling the site.
Open skill

