/blog-geo

name: blog-geo
description: >
  AI citation readiness audit as part of SEO, covering classic Google search
  and AI search surfaces together. Use whenever the user wants their content
  to rank or be cited in ChatGPT, Perplexity, Claude, Gemini, Copilot,
  You.com, Google AI Overviews, or Google AI Mode. AI citation optimization
  audit scoring blog posts for major answer surfaces. Evaluates
  evidence-backed citability, purpose clarity, entity clarity, structured
  data, and AI crawler accessibility. Suggests evidence-backed explanations and a
  0-100 AI Citation Readiness score. Use when user says "geo", "ai
  citation", "ai optimization", "citation audit", "aeo", "perplexity
  optimization", "chatgpt citation".
user-invokable: true
argument-hint: "<file-path>"
license: MIT

Blog GEO: AI Citation Optimization Audit

Scores blog posts for AI citation readiness across ChatGPT, Perplexity, Claude, Gemini, Copilot, You.com, Google AI Overviews, and Google AI Mode as one SEO workflow, not a separate discipline. Generates a 0-100 internal AI Citation Readiness heuristic with platform-specific recommendations. The score is not a calibrated probability of citation.

Google's 2026-05-15 guidance frames generative-AI optimization as SEO: no special markup, llms.txt requirement, or separate GEO/AEO playbook is required for Google visibility. Use GEO/AEO as shorthand labels only.

Cross-reference

This skill covers FLOW surface 3 (AI assistant citations: ChatGPT, Perplexity, Claude, Gemini, Copilot, You.com) and contributes to surface 2 (SERP plus AI Overviews). Surface mapping: `skills/blog/references/flow-alignment.md`.

For directly relevant AI-citation prompts (AI-supporting-pages rewrite, evidence-based quality follow-up, ChatGPT discovery, visibility prompts), see `/blog flow optimize`.

Evidence Discipline

Use numeric AI-citation benchmarks only when the report includes a source block with URL, publisher, methodology, sample size, engine or version, query class, retrieval date, and expiry date. If any field is missing, label the benchmark as directional or remove the number. Default heuristics:

• Self-contained, evidence-backed explanations can aid reuse, but Google

prescribes no passage-length or "chunking" requirement.

• Comparison tables with semantic headers may improve extractability, but do not

cite an uplift without a dated source block.

• AI Overviews coverage is methodology-dependent: cite a dated range, not a

fixed point.

Audit Process

Step 1: Read Content

Extract from the blog post:

• Full content text and word count
• Heading structure (H1, H2, H3 hierarchy)
• Individual paragraphs and their word counts
• FAQ sections (if present)
• Schema markup (JSON-LD, microdata, RDFa)
• robots.txt mentions or meta robots directives
• Any TL;DR or summary boxes
• Comparison tables and their HTML structure
• Numbered/ordered lists
• Definition-style formatting

Step 2: Evidence-Backed Citability (4 pts)

Check each section between headings for AI-extractable passages:

| Check | Criteria | |-------|----------| | Context independence | Each passage makes sense extracted from surrounding context | | Claim structure | Passages contain: specific claim + supporting evidence + source attribution | | Completeness | Passage answers a question without requiring reader to read adjacent sections |

**Scoring:** Count important sections meeting the evidence and completeness criteria. Do not score section length.

• 4 pts: 80%+ sections have citable passages
• 3 pts: 60-79%
• 2 pts: 40-59%
• 1 pt: 20-39%
• 0 pts: <20%

Step 3: Purpose Fit and Reader Utility (3 pts)

Check heading format and answer structure:

| Check | Criteria | |-------|----------| | Clear purpose | The introduction identifies the page's topic, audience, and reader task | | Useful section openings | Important sections state the point without throat-clearing | | Intent-matched format | Declarative headings, questions, FAQs, tables, and lists are used only when they fit the material |

**Scoring:**

• 3 pts: All three criteria met
• 2 pts: Two criteria met
• 1 pt: One criterion met
• 0 pts: None met

Step 4: Entity Clarity (3 pts)

Check topic consistency and disambiguation:

| Check | Criteria | |-------|----------| | Canonical topic | One unambiguous primary topic per page | | Consistent naming | Same entity name used throughout (no confusing synonyms) | | Intro statement | Clear topic statement in the introduction paragraph | | Title-content match | Title accurately reflects the content focus |

**Scoring:**

• 3 pts: All four criteria met
• 2 pts: Three criteria met
• 1 pt: One or two criteria met
• 0 pts: None met

Step 5: Content Structure for Extraction (3 pts)

Check for AI-extractable content patterns:

| Check | Criteria | |-------|----------| | Summary | Optional standalone summary when it helps the intended reader | | Comparison tables | Tables with semantic headers such as `<thead>` or clear column labels | | Ordered lists | Numbered lists for processes and step-by-step instructions | | Definition formatting | Key terms formatted with clear definition patterns | | Evidence-backed explanations | Important reusable claims carry enough context and source support |

**Scoring:**

• 3 pts: 4-5 elements present
• 2 pts: 3 elements present
• 1 pt: 1-2 elements present
• 0 pts: None present

Step 6: AI Crawler Accessibility (2 pts)

Check technical requirements for AI crawler indexing:

| Check | Criteria | |-------|----------| | Rendered content | Important content is present in the rendered DOM and accessible to the target crawler | | Google visibility | Normal crawlability and indexability for Googlebot. No special GEO/AEO file or markup is required for Google AI features | | Non-Google AI crawlers | If the site wants visibility in non-Google answer engines, check robots.txt treatment for GPTBot, ChatGPT-User, ClaudeBot, PerplexityBot, and related documented crawlers | | Schema con