alvarovillalbaa/seo-and-geo

SEO + GEO + AEO: Complete Optimization Skill

Three disciplines. One mission: make content discoverable by both humans and machines.

• SEO — Rank in Google, Bing, and traditional search engines
• GEO — Get cited by ChatGPT, Claude, Perplexity, Gemini, and other AI assistants
• AEO — Appear as direct answers in AI Overviews, featured snippets, and voice results

These disciplines share 80% of their practices. The 20% that differs matters enormously.

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Audit Inputs

When running an audit, gather these before proceeding:

1. URL or domain — the site to audit (or a topic/keyword for keyword research mode)

2. Audit type — default to full site audit if not specified:

   • Full site audit — end-to-end SEO review covering all sections below
   • Keyword research — identify keyword opportunities for a topic or domain
   • Content gap analysis — find topics competitors rank for that the user doesn't cover
   • Technical SEO check — crawlability, speed, structured data, infrastructure
   • Competitor SEO comparison — head-to-head benchmarking against specific competitors

3. Target keywords or topics (optional)

4. Competitors (optional) — if not provided and needed, use web search to identify 2-3 likely competitors based on the domain and keyword space.

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Initial Assessment

Check for project context before starting:

1. Read AGENTS.md or any product/marketing context file if present
2. Identify the site type: SaaS, e-commerce, blog, documentation, local business, media
3. Identify the primary goal: traffic, citations, brand awareness, conversions
4. Identify current weak points: technical issues, thin content, no AI visibility

Ask only what isn't in context:

• What pages/keywords are priority?
• Who are the top competitors?
• Is there access to Google Search Console?
• What's the primary audience: humans searching Google, or AI-assisted researchers?

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Which Discipline to Apply

Use this decision framework:

| Situation | Primary Focus | |-----------|---------------| | Site not ranking in Google | SEO — Technical + On-page | | Site ranks but gets no clicks | AEO — Featured snippets + SERP appeal | | Brand not mentioned by AI assistants | GEO — Content authority + citation patterns | | All three lacking | Full-stack: SEO foundation → AEO structure → GEO signals | | New page being published | All three simultaneously | | Existing page refresh | Audit first, then targeted improvements |

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The Optimization Stack

Apply in order — each layer depends on the one below:

Layer 4: GEO — AI citation authority
         ↑ requires trust signals, depth, named sources

Layer 3: AEO — Answer extraction
         ↑ requires clear structure, question-answer format

Layer 2: On-page SEO — Relevance signals
         ↑ requires crawlable, indexable content

Layer 1: Technical SEO — Foundation
         (crawlability, speed, indexation)

Fix technical issues before optimizing content. Fix on-page before chasing AI citations.

Writing new SEO content? Use the content-writing skill — it includes the full SEO writing workflow: CORE-EEAT pre-write checklist, keyword map, title optimization (3 options), meta description, featured snippet formatting, and on-page SEO self-check. This skill (seo-and-geo) focuses on auditing and optimization of existing content and sites.

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Technical SEO: Foundation Checklist

Crawlability

• robots.txt does not block important pages
• XML sitemap exists, is valid, and submitted to Search Console
• No redirect chains (A→B→C — consolidate to A→C)
• No soft 404s returning 200 status
• Important pages reachable within 3 clicks from homepage

AI Bot Access (critical for GEO — verify these bots are allowed in robots.txt):

• GPTBot and ChatGPT-User (ChatGPT)
• PerplexityBot (Perplexity)
• ClaudeBot and anthropic-ai (Claude)
• Bingbot (Copilot/Bing)
• Google-Extended (Google Gemini and AI Overviews)
• Applebot-Extended (Apple Intelligence)

robots.txt template — allows all AI search bots while blocking training-only crawlers:

User-agent: GPTBot
User-agent: ChatGPT-User
User-agent: PerplexityBot
User-agent: ClaudeBot
User-agent: anthropic-ai
User-agent: Google-Extended
User-agent: Bingbot
Allow: /

# Block training-only (won't affect citations)
User-agent: CCBot
Disallow: /

Quick check: curl -s "https://example.com/robots.txt"

Indexation

• Canonical tags on all pages (<link rel="canonical">)
• No noindex on pages that should rank
• www/non-www and HTTP/HTTPS consistency
• Trailing slash consistency across the site

Core Web Vitals (Google ranking factor)

• LCP (Largest Contentful Paint) < 2.5s
• INP (Interaction to Next Paint) < 200ms
• CLS (Cumulative Layout Shift) < 0.1

Mobile-first

• Responsive design (not separate m.site)
• Same content served to mobile and desktop
• Tap targets ≥ 48px
• Viewport meta tag configured

For deep technical SEO: see references/technical-seo.md

For Next.js/React implementation: see references/nextjs-implementation.md

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Technical SEO: Full Audit Process (9-Step)

Use this structured workflow when performing a dedicated technical SEO audit. Produces a scored health report (0–100) with critical/high/medium issue triage and a prioritized implementation roadmap.

Inputs needed: URL or domain, robots.txt/sitemap access, PageSpeed Insights data (or screenshots).

Step 1: Audit Crawlability

## Crawlability Analysis

### Robots.txt Review

**URL**: [domain]/robots.txt
**Status**: [Found/Not Found/Error]

| Check | Status | Notes |
|-------|--------|-------|
| File exists | ✅/❌ | [notes] |
| Valid syntax | ✅/⚠️/❌ | [errors found] |
| Sitemap declared | ✅/❌ | [sitemap URL] |
| Important pages blocked | ✅/⚠️/❌ | [blocked paths] |
| Assets blocked | ✅/⚠️/❌ | [CSS/JS blocked?] |
| Correct user-agents | ✅/⚠️/❌ | [notes] |

**Issues Found**: [list]
**Recommended robots.txt**: [provide corrected version if needed]

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### XML Sitemap Review

**Sitemap URL**: [URL]  **Status**: [Found/Not Found/Error]

| Check | Status | Notes |
|-------|--------|-------|
| Sitemap exists | ✅/❌ | |
| Valid XML format | ✅/⚠️/❌ | [errors] |
| In robots.txt | ✅/❌ | |
| Submitted to Search Console | ✅/⚠️/❌ | |
| URLs count | [X] | [appropriate?] |
| Only indexable URLs | ✅/⚠️/❌ | |
| Includes lastmod (accurate) | ✅/⚠️ | |

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### Crawl Budget Analysis

| Factor | Status | Impact |
|--------|--------|--------|
| Crawl errors | [X] errors | [Low/Med/High] |
| Duplicate content | [X] pages | [Low/Med/High] |
| Redirect chains | [X] found | [Low/Med/High] |
| Orphan pages | [X] found | [Low/Med/High] |

**Crawlability Score**: [X]/10

Step 2: Audit Indexability

## Indexability Analysis

### Index Status Overview

| Metric | Count | Notes |
|--------|-------|-------|
| Pages in sitemap | [X] | |
| Pages indexed | [X] | [source: site: search] |
| Index coverage ratio | [X]% | [good if >90%] |

### Index Blockers Check

| Blocker Type | Found | Pages Affected |
|--------------|-------|----------------|
| noindex meta tag | [X] | [list or "none"] |
| noindex X-Robots | [X] | [list or "none"] |
| Robots.txt blocked | [X] | [list or "none"] |
| Canonical to other | [X] | [list or "none"] |
| 4xx/5xx errors | [X] | [list or "none"] |
| Redirect loops | [X] | [list or "none"] |

### Canonical Tags Audit

| Check | Status | Notes |
|-------|--------|-------|
| Canonicals present | ✅/⚠️/❌ | [X]% of pages |
| Self-referencing on unique pages | ✅/⚠️/❌ | |
| Consistent (HTTP/HTTPS) | ✅/⚠️/❌ | |
| Consistent (www/non-www) | ✅/⚠️/❌ | |

### Duplicate Content Issues

| Issue Type | Count | Examples |
|------------|-------|----------|
| URL-based duplicates | [X] | [URLs] |
| Parameter duplicates | [X] | [URLs] |
| WWW/non-WWW | [X] | [notes] |

**Indexability Score**: [X]/10

Steps 3–9 (use reference templates)

For detailed output templates for each step, see references/technical-audit-templates.md:

3. Site Speed & Core Web Vitals — LCP/FID/CLS/INP, TTFB, FCP, resource loading breakdown, optimization recommendations
4. Mobile-Friendliness — Mobile-friendly test, responsive design, mobile-first indexing verification
5. Security & HTTPS — SSL certificate, HTTPS enforcement, mixed content, HSTS, security headers
6. URL Structure — URL patterns, dynamic params, session IDs, redirect chains and loops
7. Structured Data — Schema markup validation, missing schema opportunities
8. International SEO — Hreflang implementation, language/region targeting (if applicable)
9. Audit Summary — Overall health score (0–100), critical/high/medium issue triage, quick wins, 4-week implementation roadmap, monitoring recommendations

Validation Checkpoints

• Every recommendation cites specific data points (not generic advice)
• All issues include affected URLs or page counts
• Performance metrics include actual numbers with units (seconds, KB)
• Source of each data point clearly stated (crawl data, PageSpeed, user-provided, or estimated)

Issue Severity Framework

| Severity | Examples | Response Time | |----------|---------|---------------| | Critical | robots.txt blocking site, noindex on key pages, site-wide 500 errors | Same day | | High | Slow page speed, missing hreflang, duplicate content, redirect chains | Within 1 week | | Medium | Missing schema, suboptimal canonicals, thin content pages | Within 1 month | | Low | Minor CLS issues, non-essential schema missing | Next quarter |

Reference files:

• references/technical-audit-example.md — Full worked example (cloudhosting.com audit) and comprehensive checklist
• references/http-status-codes.md — HTTP status codes SEO impact, redirect best practices, crawl budget
• references/robots-txt-reference.md — robots.txt syntax guide, platform templates, common mistakes, emergency fixes

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On-Page SEO: Relevance Signals

Title tag (50-60 characters)

• Primary keyword in first half
• Unique per page
• Compelling reason to click

Meta description (150-160 characters)

• Includes primary keyword
• States specific value: what the user will learn/get
• Starts with an action verb (not "Master")

Heading structure

• Single H1 with primary keyword
• Logical hierarchy: H1 → H2 → H3 (no skipping levels)
• H2s answer real user questions ("What is X?", "How does X work?")

Content

• Primary keyword in first 100 words
• Topic fully covered (not just surface-level)
• Satisfies search intent: informational / commercial / transactional / navigational
• Better depth than current top-ranking competitors

Images

• Descriptive filename (closures-javascript-example.png not img001.png)
• Alt text describes the image meaningfully
• WebP format, compressed, lazy-loaded

Internal linking

• Minimum 3-5 contextual links to related content per page
• Descriptive anchor text (not "click here" or "read more")
• No orphan pages (every page linked from at least one other)

For content strategy: see references/content-optimization.md

Per-Page Audit: 11-Step Workflow

When auditing a single page, follow this sequence and produce structured output for each step:

1. Gather page info — URL, target keyword(s), page type (blog/product/landing/service), business goal
2. Title tag — length (50-60 chars), keyword in first half, uniqueness, compelling copy
3. Meta description — length (150-160 chars), keyword, CTA, uniqueness
4. Header structure — single H1 with keyword, logical H1→H2→H3 hierarchy, keyword variations in H2s
5. Content quality — word count vs. query-type benchmark, comprehensiveness, E-E-A-T signals, formatting
6. Keyword usage — placement across title/H1/first 100 words/URL/alt text; density 0.5-2.5%; LSI terms
7. Internal links — count (3-5+ per 1,000 words), anchor text quality, relevance, broken links
8. Images — alt text on all images, descriptive filenames, file sizes (<200KB), WebP format, lazy loading
9. Technical on-page — URL structure, canonical tag, mobile-friendly, LCP, HTTPS, schema type
10. CORE-EEAT quick scan — 17 on-page-relevant E-E-A-T items (see template in reference file)
11. Audit summary — overall score (0-100), priority issues (critical/important/minor), quick wins, action checklist

Scoring weights (section → points):

| Section | Weight | Max | |---------|--------|-----| | Title Tag | 15% | 15 pts | | Meta Description | 5% | 5 pts | | Header Structure | 10% | 10 pts | | Content Quality | 25% | 25 pts | | Keyword Optimization | 15% | 15 pts | | Internal/External Links | 10% | 10 pts | | Image Optimization | 10% | 10 pts | | Page-Level Technical | 10% | 10 pts |

Content length benchmarks (for "sufficient length" scoring):

| Query Type | Min for full marks | Minimum | |-----------|-------------------|---------| | Informational | 1,500+ words | 500 words | | Commercial | 1,200+ words | 400 words | | Transactional | 500+ words | 200 words | | Local | 400+ words | 150 words |

Keyword density: 0.5-1.0% ideal; 1.0-2.5% acceptable; >3.0% = keyword stuffing (penalized, fix immediately).

For detailed step-by-step output templates (steps 1-11), scoring rubric with calibration examples, issue resolution playbook, and page-type checklists: see references/on-page-audit.md

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AEO: Answer Engine Optimization

AEO wins featured snippets, AI Overviews, and voice results. The goal: make answers easy to extract.

Definition pattern (for "What is X?" queries):

## What is [Term]?

[Term] is [1-sentence definition]. [2-3 sentences of context explaining why it matters].

Target: 40-60 words. Google extracts this for paragraph featured snippets.

Step-by-step pattern (for "How to X?" queries):

## How to [Action]

[Brief overview sentence]

1. **[Step Name]**: [Clear action, 1-2 sentences]
2. **[Step Name]**: [Clear action, 1-2 sentences]
3. **[Step Name]**: [Clear action, 1-2 sentences]

Comparison table pattern (for "X vs Y" queries):

| Feature | Option A | Option B |
|---------|----------|----------|
| [Key dimension] | [Value] | [Value] |
| Best for | [Use case] | [Use case] |

FAQ pattern (for "People Also Ask" boxes):

## Frequently Asked Questions

### [Question exactly as users would search it]?

[Direct answer in first sentence]. [Supporting context in 2-3 more sentences].

Key AEO principles:

• Answer the question in the first sentence after the question heading
• Keep definitions to 40-60 words
• Use numbered lists for sequential processes
• Use bullet lists for unordered sets of items
• Add FAQ schema markup for FAQ sections

For complete AEO patterns with examples: see references/content-optimization.md

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GEO: Generative Engine Optimization

GEO is the practice of making content citation-worthy for AI systems (ChatGPT, Claude, Perplexity, Gemini, AI Overviews).

The core insight: AI systems cite sources that demonstrate clear authority, contain verifiable facts, and are structured for extraction.

Five GEO signals:

1. Named attribution — Quote real experts with names and credentials

   "According to [Expert Name], [Title] at [Organization], [specific claim]."

2. Cited statistics — Include numbers with sources and dates

   "According to [Source], [specific statistic], as of [year]."

3. Self-contained statements — Write sentences that make sense without surrounding context

   "The optimal length for SEO blog posts is 1,500-2,500 words for competitive topics."

4. Topical depth — Cover a topic comprehensively (AI systems prefer authoritative sources over thin ones)

5. Freshness signals — Include publication dates, update dates, version numbers where relevant

Princeton Research: 9 Optimization Methods (validated on Perplexity AI, KDD 2024):

| Method | Visibility Boost | How to Apply | |--------|-----------------|--------------| | Cite Sources | +40% | Add authoritative citations and references | | Statistics Addition | +37% | Include specific numbers and data points | | Quotation Addition | +30% | Add expert quotes with attribution | | Authoritative Tone | +25% | Use confident, expert language | | Easy-to-understand | +20% | Simplify complex concepts | | Technical Terms | +18% | Include domain-specific terminology | | Unique Words | +15% | Increase vocabulary diversity | | Fluency Optimization | +15-30% | Improve readability and flow | | ~~Keyword Stuffing~~ | -10% | AVOID — hurts AI visibility |

Best combination: Fluency + Statistics = maximum boost. Low-ranking sites can gain up to +115% visibility with citations.

Content trust signals:

• Author byline with credentials or bio
• Publication/last-updated date
• External citations and references
• HTTPS secure site
• Organization information (About page, contact info)

Third-party presence matters more than your own site:

AI systems don't only cite your domain — they cite where you appear across the web. Brands are 6.5× more likely to be cited via third-party sources than their own domains.

| Source | ChatGPT Citation Share | Action | |--------|----------------------|--------| | Wikipedia | 7.8% | Keep your Wikipedia page accurate and current | | Reddit | 1.8% | Participate authentically in relevant communities | | Forbes/major publications | 1.1% | Pitch guest posts and expert commentary | | Review platforms (G2, Capterra) | Significant for SaaS | Maintain updated profiles | | YouTube | Cited heavily by Google AI Overviews | Create how-to video content |

Key stat: Traditional SEO gets you ranked. AI SEO gets you cited. A page ranking on page 2 can still get cited if it has strong structure and authority signals — only ~15% of AI Overview sources overlap with the traditional Top 10.

Avoid AI-generated writing patterns — AI systems are increasingly trained to discount content that looks machine-generated. See references/ai-signals.md for patterns to avoid.

For Princeton GEO research details and domain-specific recommendations: see references/geo-research.md

For deep GEO strategies by content domain: see references/geo-strategies.md

For GEO writing patterns (statistic blocks, expert quote blocks, evidence sandwiches, domain-specific tactics): see references/content-patterns.md

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Structured Data: Schema Markup

Schema markup directly communicates content meaning to search engines and AI systems.

Always implement:

• Organization on homepage
• WebSite with SearchAction on homepage
• BreadcrumbList on all pages
• Article on blog posts
• FAQPage on FAQ sections
• HowTo on step-by-step guides

For complete schema templates and JSON-LD: see references/structured-data.md

For Next.js implementation (JsonLd component, builder utilities): see references/nextjs-implementation.md and examples/nextjs-metadata.ts

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E-E-A-T: The Trust Foundation

Google's E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) applies equally to traditional search ranking and AI citation decisions.

| Signal | SEO Impact | GEO Impact | |--------|------------|------------| | Author credentials | Medium | High | | First-hand experience | High | High | | External citations | High | Very High | | Publication date/freshness | Medium | High | | Organizational transparency | Medium | Very High | | Accurate, verifiable claims | High | Very High |

Implement E-E-A-T:

• Add author bios with real credentials
• Include case studies or first-person experience
• Cite external authoritative sources
• Show publication and update dates
• Add organizational contact information and About page
• Link out to primary sources (studies, official docs, government data)

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AI Visibility Audit

Before optimizing, assess current AI search presence. Run this before any GEO work.

Step 1: Manual check across platforms

Test 10-20 priority queries in ChatGPT, Perplexity, and Google. For each:

• Does an AI answer appear?
• Are you cited? If not, who is?
• What pages get cited? (Check content structure, authority signals, freshness)

Step 2: Content extractability check (run on each priority page)

| Check | Pass/Fail | |-------|-----------| | Clear definition in first paragraph? | | | Self-contained answer blocks (work without surrounding context)? | | | Statistics with sources cited? | | | Comparison tables for "[X] vs [Y]" queries? | | | FAQ section with natural-language questions? | | | Schema markup (FAQ, HowTo, Article, Product)? | | | Expert attribution (author name, credentials)? | | | Recently updated (within 6 months)? | | | Heading structure matches query patterns? | | | AI bots allowed in robots.txt? | |

Step 3: Verify robots.txt (see Technical SEO section above for bot list)

Step 4: Check Brave Search for Claude visibility — search your brand at search.brave.com (Claude uses Brave, not Google).

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Platform-Specific Optimization

Each AI platform has distinct ranking signals. Target the highest-priority ones first.

| Platform | Primary Index | #1 Factor | Unique Requirement | |----------|--------------|-----------|-------------------| | ChatGPT | Web (Bing-based) | Domain Authority | Content-Answer Fit (55%) | | Perplexity | Own + Google | Semantic Relevance | FAQ Schema + allow PerplexityBot | | Google AI Overview | Google | E-E-A-T | Authoritative citations (+132% visibility) | | Microsoft Copilot | Bing | Bing Index | Submit to Bing Webmaster Tools | | Claude AI | Brave Search | Factual Density | Brave Search indexing (not Google) |

Key stats:

• ChatGPT: content updated within 30 days gets 3.2× more citations; >350K referring domains = 8.4 avg citations
• Google AI Overview: appears in 85%+ of searches; 340% visibility boost from SGE-optimized content
• Claude uses Brave Search (crawl-to-cite ratio: 38,065:1 — quality is critical)

Critical stats:

• AI Overviews reduce clicks to websites by up to 58% — optimize for citation, not just ranking
• Content updated within 30 days gets 3.2× more ChatGPT citations
• Optimized content gets cited 3× more often than non-optimized

For detailed per-platform ranking algorithms and optimization checklists: see references/platform-algorithms.md

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Content Types That Get Cited Most

Not all content is equally citable. Prioritize these when creating or refreshing:

| Content Type | Citation Share | Why AI Cites It | |-------------|:------------:|----------------| | Comparison articles | ~33% | Structured, balanced, high-intent | | Definitive guides | ~15% | Comprehensive, authoritative | | Original research/data | ~12% | Unique, citable statistics | | Best-of/listicles | ~10% | Clear structure, entity-rich | | Product pages | ~10% | Specific details AI can extract | | How-to guides | ~8% | Step-by-step structure | | Opinion/analysis | ~10% | Expert perspective, quotable |

Underperformers for AI citation: Generic blog posts without structure, thin product pages with marketing fluff, gated content (AI can't access it), content without dates or author attribution.

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AI SEO by Content Type

SaaS Product Pages

Goal: Get cited in "What is [category]?" and "Best [category]" queries.

• Clear product description in first paragraph (what it does, who it's for)
• Feature comparison tables (you vs. category, not just competitors)
• Specific metrics ("processes 10,000 transactions/sec" not "blazing fast")
• Pricing transparency — AI cites pages with visible pricing
• FAQ section addressing common buyer questions

Blog Content

Goal: Get cited as an authoritative source on topics in your space.

• One clear target query per post (match H2 heading to query)
• Definition in first paragraph for "What is" queries
• Original data, research, or expert quotes
• "Last updated" date visible with author bio

Comparison/Alternative Pages

Goal: Get cited in "[X] vs [Y]" and "Best [X] alternatives" queries.

• Structured comparison tables (not just prose)
• Fair and balanced — AI penalizes obviously biased comparisons
• Specific criteria with ratings or scores
• Updated pricing and feature data

Documentation / Help Content

Goal: Get cited in "How to [X] with [your product]" queries.

• Step-by-step format with numbered lists
• Code examples where relevant
• HowTo schema markup
• Clear prerequisites and expected outcomes

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Keyword Research Workflow

When a user requests keyword research, follow these steps:

1. Understand the Context

   Ask clarifying questions if not already provided:

   • What is your product/service/topic?
   • Who is your target audience?
   • What is your business goal? (traffic, leads, sales)
   • What is your current domain authority? (new site, established, etc.)
   • Any specific geographic targeting? Preferred language?

2. Generate Seed Keywords

   Start with:

   • Core product/service terms
   • Problem-focused keywords (what issues do you solve?)
   • Solution-focused keywords (how do you help?)
   • Audience-specific terms and industry terminology

3. Expand Keyword List

   For each seed keyword, generate variations:

   • Modifiers: Best [keyword], Top [keyword], [keyword] for [audience], How to [keyword], What is [keyword], [keyword] vs [alternative], [keyword] examples, [keyword] tools
   • Long-tail: [keyword] for beginners, [keyword] for small business, Free [keyword], [keyword] guide, [keyword] checklist, [keyword] template

4. Classify Search Intent

   Categorize each keyword:

   | Intent | Signals | Example | Content Type | |--------|---------|---------|--------------| | Informational | what, how, why, guide, learn | "what is SEO" | Blog posts, guides | | Navigational | brand names, specific sites | "google analytics login" | Homepage, product pages | | Commercial | best, review, vs, compare | "best SEO tools 2026" | Comparison posts, reviews | | Transactional | buy, price, discount, order | "buy SEO software" | Product pages, pricing |

   For the full intent taxonomy with sub-categories, SERP feature correlations, funnel alignment, and mixed intent patterns: see references/keyword-intent-taxonomy.md

5. Assess Keyword Difficulty

   Score each keyword (1–100 scale):

   • High (70–100): Major brands ranking, high DA competitors, established content (1000+ backlinks), paid ads dominating SERP
   • Medium (40–69): Mix of authority and niche sites, moderate backlink requirements
   • Low (1–39): Few authoritative competitors, thin or outdated content, long-tail variations, new/emerging topics

6. Calculate Opportunity Score

   Formula: Opportunity = (Volume × Intent Value) / Difficulty

   Intent Value: Informational = 1, Navigational = 1, Commercial = 2, Transactional = 3

   | Scenario | Volume | Difficulty | Intent | Priority | |----------|--------|------------|--------|----------| | Quick Win | Low–Med | Low | High | ⭐⭐⭐⭐⭐ | | Growth | High | Medium | High | ⭐⭐⭐⭐ | | Long-term | High | High | High | ⭐⭐⭐ | | Research | Low | Low | Low | ⭐⭐ |

   For the weighted priority scoring matrix (5-factor scores), priority categories (P0–P3), and seasonal keyword patterns: see references/keyword-prioritization-framework.md

7. Identify GEO Opportunities

   Keywords likely to trigger AI responses:

   • High GEO potential: Question formats ("What is...", "How does..."), definition queries ("[term] meaning"), comparison queries ("[A] vs [B]"), list queries ("best [category]"), how-to queries
   • AI answer indicators: Factual/definitional query, answer can be summarized concisely, topic is well-documented, low commercial intent

8. Create Topic Clusters

   Group keywords into pillar + cluster content:

   Pillar: Comprehensive guide (head keyword, broad scope)
     ├── Cluster 1: Deep subtopic page → links back to pillar
     ├── Cluster 2: Deep subtopic page → links back to pillar
     └── Cluster N: Deep subtopic page → links back to pillar
   

   Rules: Every cluster links to the pillar; the pillar links to every cluster; cluster pages link to 2–3 related siblings.

   For planning worksheets, hub-and-spoke architecture patterns (Classic, Layered, Use-Case, Process), internal linking density guides, content calendar integration, and cluster health scorecards: see references/topic-cluster-templates.md

9. Generate Output Report

   Produce a report containing: Executive Summary, Top Keyword Opportunities (Quick Wins, Growth, GEO), Topic Clusters, Content Calendar, and Next Steps.

   For the complete report template and a worked example (project management software): see examples/keyword-research-example-report.md

Keyword Research Validation Checkpoints

Input:

• [ ] Seed keywords or topic description clearly provided
• [ ] Target audience and business goals specified
• [ ] Geographic and language targeting confirmed
• [ ] Domain authority or site maturity level established

Output:

• [ ] Every recommendation cites specific data points (not generic advice)
• [ ] Search volume and difficulty scores included for each keyword
• [ ] Keywords grouped by intent and mapped to content types
• [ ] Topic clusters show clear pillar-to-cluster relationships
• [ ] Source of each data point stated (tool data, user-provided, or estimated)

Keyword mapping principle: One primary keyword cluster per page. Prevent cannibalization (multiple pages competing for the same keyword).

People Also Ask mining — Always pull PAA questions from Google for the target topic; these are high-AEO opportunities.

Zero-click awareness — Some queries will never drive clicks; optimize those for AI citation and brand awareness instead.

When SEO tools are connected (Ahrefs, Semrush MCP):

• Pull keyword data, search volume, and difficulty scores automatically
• Identify keywords the site currently ranks for and where it's gaining/losing ground
• Cross-reference with analytics to validate which keywords drive conversions

When tools are not connected: Use web search for the keyword landscape. Note to user: "For precise volume and difficulty data, connect an SEO tool like Ahrefs or Semrush via MCP."

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Content Gap Analysis

Identify what's missing from the content strategy:

• Competitor topic coverage — topics and keywords competitors rank for that the site doesn't cover
• Content freshness — pages not updated in 12+ months that may be losing rankings
• Thin content — pages with insufficient depth (under 300 words for informational queries, lacking substance)
• Missing content types — formats competitors use but the site doesn't (guides, comparison pages, glossaries, tools, templates)
• Funnel gaps — missing content at specific buyer journey stages (awareness, consideration, decision)
• Topic clusters — opportunities to build pillar pages with supporting content

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Competitor SEO Comparison

For each competitor, compare:

• Keyword overlap — keywords both sites rank for, and where each ranks higher
• Keyword gaps — terms the competitor ranks for that the user does not
• Domain authority signals — relative strength based on backlink profiles, referring domains, and content depth
• Content depth — average content length, topic coverage breadth, publishing frequency
• Backlink profile — types of sites linking to competitors, link-worthy content they've produced
• SERP feature ownership — which competitor appears in featured snippets, People Also Ask, image packs, or knowledge panels
• Technical advantages — site speed differences, mobile experience, structured data usage

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Off-Page SEO: Backlink Building

Backlinks remain one of the strongest SEO ranking signals. The most sustainable strategy is earning editorial links through genuinely useful content. The fastest ethical path to new links is the broken link method: find dead links on high-authority pages in your niche, then pitch your content as the replacement.

Why it works:

• Webmasters have a concrete reason to act (fixing a broken link)
• You're targeting pages that already link out on your topic
• Response rates are 3–5× higher than cold content pitches

Broken Link Outreach Workflow (5-Step)

Requirements: web_search, web_fetch, ability to send email

Parameters:

• niche_keywords — describe your content domain (e.g., "content marketing", "python testing")
• your_content_urls — your best pages to pitch as replacements
• min_domain_authority — skip low-DA sites (default: 30)

Step 1 — Find resource pages

Search for high-authority link pages in your niche:

"{{niche_keywords}}" inurl:resources
"{{niche_keywords}}" inurl:links
"{{niche_keywords}}" "useful resources" OR "further reading"

Step 2 — Extract and check outbound links

For each resource page:

1. Fetch the full HTML and extract all external <a href> links
2. Filter out social media domains, CDNs, and the host's own domain
3. Issue HEAD requests for each link; flag anything returning 404, 410, or connection timeout

Step 3 — Match dead links to your content

For each broken link, analyze:

• The anchor text and surrounding context
• The original URL path/slug (even if dead, it reveals the topic)
• Match semantically to your your_content_urls; only proceed when there's a strong topical fit

Step 4 — Find site owner contact

Search for: site:{{domain}} contact OR email OR "get in touch"

Priority order: dedicated contact page → author bio email → site footer → WHOIS (last resort)

Step 5 — Draft and send outreach

Use this template (personalize before sending):

Subject: Broken link on [page title]

Hi [Name],

I was browsing your [topic] resources page and noticed the link to
"[dead link anchor text]" appears to be broken (returns a 404).

I recently published a comprehensive guide on [same topic] that might
work as a replacement: [your_url]

[One sentence explaining why your content is a good fit — word count,
recency, specific sub-topic it covers]

Either way, wanted to give you a heads up about the broken link!

[Your name]

Follow-up: Send one follow-up after 3–4 days if no response. Do not send more than two emails total.

Automated Execution (Agentic)

For a fully automated broken-link campaign run by an AI agent:

Trigger: weekly (e.g., Monday 6am)
Agent capabilities needed: web_search, web_fetch, email
State file: track contacted domains to avoid duplicates

See references/backlink-hunter.md for the complete automated workflow specification including search queries, link extraction logic, LLM-powered outreach drafting, and state management.

For analyzing your existing backlink profile:

python3 scripts/backlinks.py "example.com" --limit 20

Link Building Quality Signals

Sites worth targeting (high-DA, editorial context):

• University or government .edu/.gov resource pages
• Industry association "recommended tools/resources" pages
• Popular listicles in your niche that are 2+ years old (higher chance of dead links)
• Documentation hubs and developer wikis

Sites to skip:

• Link directories with no editorial curation
• Sites with DA < 30 (little ranking value)
• Sites with clearly auto-generated content
• Sites in unrelated niches (no topical relevance)

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Common Mistakes

• Ignoring AI search — AI Overviews appear in ~45% of Google searches; ChatGPT/Perplexity are growing fast
• Treating AI SEO as separate from traditional SEO — Good technical SEO is the foundation; AI SEO adds structure and authority on top
• No freshness signals — Undated content loses to dated content because AI weights recency. Always show publication/update dates
• Gating your best content — AI can't access it; keep authoritative content open
• Ignoring third-party presence — A Wikipedia mention may generate more AI citations than your own blog
• No structured data — Schema markup gives AI structured context; content with proper schema shows 30-40% higher AI visibility
• Keyword stuffing — Unlike traditional SEO where it's just ineffective, keyword stuffing actively reduces AI visibility by 10% (Princeton GEO study)
• Blocking AI bots — If GPTBot, PerplexityBot, Google-Extended, or ClaudeBot are blocked, those platforms can't cite you
• Generic claims without data — "We're the best" won't get cited. "Our customers see 3× improvement in [metric]" will
• Not monitoring — You can't improve what you don't measure; check AI visibility monthly at minimum

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Output Format

Executive Summary

Open with a 3-5 sentence summary of overall SEO health. Highlight:

• The site's biggest strength
• The top 3 priorities that will have the most impact
• An overall assessment: strong foundation, needs work, or critical issues

Keyword Opportunity Table

| Keyword | Est. Difficulty | Opportunity Score | Current Ranking | Intent | Recommended Content Type | |---------|----------------|-------------------|-----------------|--------|--------------------------|

Opportunity score: high, medium, or low — based on search demand, difficulty, and business relevance. Include 15-25 opportunities sorted by opportunity score.

On-Page Issues Table

| Page | Issue | Severity | Recommended Fix | |------|-------|----------|-----------------|

Severity levels:

• Critical — directly hurting rankings or preventing indexation
• High — significant impact on SEO performance
• Medium — best practice violation, moderate impact
• Low — minor optimization opportunity

On-Page Score Summary (single-page audits)

When auditing one specific page, open the audit report with a visual score breakdown:

## Overall Score: [X]/100

Score Breakdown:
████████░░ Title Tag:        [X]/10  (15%)
██████░░░░ Meta Description: [X]/10  ( 5%)
█████████░ Headers:          [X]/10  (10%)
███████░░░ Content:          [X]/10  (25%)
████████░░ Keywords:         [X]/10  (15%)
█████░░░░░ Internal Links:   [X]/10  (10%)
██████░░░░ Images:           [X]/10  (10%)
███████░░░ Technical:        [X]/10  (10%)

Grade scale: 90-100 = A+, 80-89 = A, 70-79 = B, 60-69 = C, 50-59 = D, <50 = F

CORE-EEAT Quick Scan (single-page audits)

Include this scan before priority issues. Score each item ✅ pass / ⚠️ partial / ❌ fail:

| ID | Check Item | Status | |----|-----------|--------| | C01 | Intent Alignment — title promise matches content delivery | | | C02 | Direct Answer — core answer in first 150 words | | | C09 | FAQ Coverage — structured FAQ section present | | | C10 | Semantic Closure — conclusion answers the opening | | | O01 | Heading Hierarchy — H1→H2→H3, no skipped levels | | | O02 | Summary Box — TL;DR or Key Takeaways block | | | O03 | Data Tables — comparisons use tables, not prose | | | O05 | Schema Markup — appropriate JSON-LD implemented | | | O06 | Section Chunking — single topic per section | | | R01 | Data Precision — ≥5 precise numbers in content | | | R02 | Citation Density — ≥1 external citation per 500 words | | | R06 | Timestamp — last updated within 1 year | | | R08 | Internal Link Graph — descriptive anchor text throughout | | | Exp01 | First-Person Narrative — "I tested" or "We found" signals | | | Ept01 | Author Identity — byline + bio present | | | T04 | Disclosure Statements — affiliate/sponsored links disclosed | |

Score: [X]/16 items passing

Page-Type Quick Checklists

Blog post: keyword in title + meta, single H1, 1,500+ words, 3+ internal links, all images have alt, FAQ section + schema, author bio with credentials

Product page: product name in title, price/availability in meta description, Product schema, multiple product images with alt, customer reviews visible, related products linked

Landing page: keyword-optimized title, benefit-focused meta, clear H1 value proposition, trust signals (testimonials, logos), single primary CTA, LCP ≤2.5s, fully mobile-responsive

GEO/AEO Opportunities

| Opportunity | How to Capitalize | Expected Impact | |------------|-------------------|-----------------|

Content Gap Recommendations

For each content gap, provide:

• Topic or keyword to target
• Why it matters — search demand, competitor coverage, funnel stage
• Recommended format — blog post, landing page, guide, comparison page
• Priority — high, medium, or low
• Estimated effort — quick win (1-2 hours), moderate (half day), substantial (multi-day)

Technical SEO Checklist

| Check | Status | Details | |-------|--------|---------|

Status: Pass, Fail, or Warning.

Competitor Comparison Summary

| Dimension | Your Site | Competitor A | Competitor B | Winner | |-----------|-----------|--------------|--------------|--------|

Include rows for: keyword count, content depth, publishing frequency, backlink signals, technical score, SERP feature presence.

Prioritized Action Plan

Quick Wins (do this week):

• Actions that take under 2 hours and have immediate impact
• Examples: fix title tags, add meta descriptions, fix broken links, add alt text

Strategic Investments (plan for this quarter):

• Actions requiring more effort but driving long-term growth
• Examples: build a topic cluster, create a pillar page, launch a link-building campaign

For each action item: what to do (specific), expected impact (high/medium/low), effort estimate, dependencies.

For implementing optimizations:

• Provide exact copy for title tags, meta descriptions
• Provide working code for schema markup
• Provide content templates for AEO patterns
• Verify fixes against checklists in references

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Measurement

Traditional SEO:

• Google Search Console — impressions, clicks, average position, Core Web Vitals
• PageSpeed Insights — Core Web Vitals field data
• Rich Results Test — validate structured data

AI Visibility Monitoring tools:

| Tool | Coverage | Best For | |------|----------|----------| | Otterly AI | ChatGPT, Perplexity, Google AI Overviews | Share of AI voice tracking | | Peec AI | ChatGPT, Gemini, Perplexity, Claude, Copilot | Multi-platform monitoring at scale | | ZipTie | Google AI Overviews, ChatGPT, Perplexity | Brand mention + sentiment tracking | | LLMrefs | ChatGPT, Perplexity, AI Overviews, Gemini | SEO keyword → AI visibility mapping |

DIY monitoring (no tools): Monthly, pick your top 20 queries → run each through ChatGPT, Perplexity, and Google → record: are you cited? Who is? Which page? → track month-over-month in a spreadsheet.

For full measurement framework and KPIs: see references/measurement.md

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CORE-EEAT Content Quality Audit

The CORE-EEAT framework scores content across 80 criteria in 8 dimensions — producing both a GEO Score (AI citation potential) and an SEO Score (source credibility). Use this when you need more than the 16-item quick scan in per-page audits.

When to Use Full 80-Item Audit

• Content isn't getting cited by AI systems despite good technical SEO
• Benchmarking content quality against competitors
• Before/after comparison for a content refresh
• Evaluating whether a page meets "helpful content" standards

Scoring System

| Result | Points | |--------|--------| | Pass | 10 | | Partial | 5 | | Fail | 0 |

• GEO Score = (C + O + R + E) / 4 — measures AI citation readiness
• SEO Score = (Exp + Ept + A + T) / 4 — measures source credibility
• Weighted Score = dimension scores × content-type weights (varies by page type)

Rating scale: 90–100 Excellent | 75–89 Good | 60–74 Medium | 40–59 Low | 0–39 Poor

Veto items — a Fail on any of these caps the total at Low:

• T04 — Affiliate links without disclosure
• C01 — Clickbait (title doesn't match content)
• R10 — Data contradicts itself

Quick-Reference: 8 Dimensions

| System | Dim | Name | GEO/SEO | Core Question | |--------|-----|------|---------|---------------| | CORE | C | Contextual Clarity | GEO 🎯 | Does the content clearly answer user intent? | | CORE | O | Organization | GEO 🎯 | Is content structured for humans and machines? | | CORE | R | Referenceability | GEO 🎯 | Can AI verify and cite the claims? | | CORE | E | Exclusivity | GEO 🎯 | Does content offer something unavailable elsewhere? | | EEAT | Exp | Experience | SEO 🔍 | Does author demonstrate real-world experience? | | EEAT | Ept | Expertise | SEO 🔍 | Does author demonstrate professional expertise? | | EEAT | A | Authority | SEO 🔍 | Is author/org recognized as an authority? | | EEAT | T | Trust | SEO 🔍 | Does the site meet trust and safety standards? |

Top 6 GEO-First Items (Fix These First)

| Rank | ID | Name | Action | |------|----|------|--------| | 1 | C02 | Direct Answer | Put core answer in first 150 words | | 2 | C09 | FAQ Coverage | Add structured FAQ with FAQPage schema | | 3 | O03 | Data Tables | Replace prose comparisons with HTML tables | | 4 | O05 | Schema Markup | Add correct JSON-LD for content type | | 5 | E01 | Original Data | Include first-party statistics or research | | 6 | O02 | Summary Box | Add TL;DR or Key Takeaways section |

Audit Workflow

1. Check veto items first (T04, C01, R10) — flag and fix immediately if triggered
2. Score all 40 CORE items (content body)
3. Score all 40 EEAT items (source credibility) — mark unavailable items N/A
4. Calculate GEO Score, SEO Score, and Weighted Score by content type
5. Rank Top 5 improvements by: dimension_weight × points_lost
6. Produce action plan: quick wins (<30 min), medium effort (1–2 hours), strategic

For full 80-item checklist, content-type weight tables, Pass/Partial/Fail criteria, and calibration examples: see references/core-eeat-benchmark.md

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CITE Domain Authority Audit

The CITE framework scores domain authority across 40 criteria in 4 dimensions — Citation, Identity, Trust, and Eminence. Pairs with CORE-EEAT for a combined 120-item assessment.

When to Use

• Before launching a GEO/backlink campaign (baseline)
• Comparing domain authority against competitors
• Diagnosing why content isn't getting cited despite good quality
• Detecting manipulation signals (PBN links, penalty history)

Domain-Type Weights

| Dim | Content Publisher | E-commerce | SaaS/Tool | Authority & Institutional | |-----|:-:|:-:|:-:|:-:| | C — Citation | 40% | 20% | 25% | 45% | | I — Identity | 15% | 20% | 30% | 20% | | T — Trust | 20% | 35% | 25% | 20% | | E — Eminence | 25% | 25% | 20% | 15% |

Veto Items (Emergency Brake)

If any of these fail, the CITE Score is capped at 39 (Poor):

| ID | Check | What It Signals | |----|-------|----------------| | T03 | Link-Traffic Coherence | Bought links — link volume disproportionate to traffic | | T05 | Backlink Profile Uniqueness | PBN or link farm — shares >60% links with another domain | | T09 | Penalty History | Active Google manual action — all optimization is futile until resolved |

Diagnosis Matrix

| CITE | CORE-EEAT | Diagnosis | Next Action | |------|-----------|-----------|-------------| | High | High | Authority + quality aligned | Maintain; expand content | | High | Low | Good domain, weak content | Run CORE-EEAT audit; fix content | | Low | High | Great content, weak domain | Build backlinks; entity optimization | | Low | Low | Start from scratch | Fix content quality first |

For full 40-item checklist, all dimension criteria, and scoring workflow: see references/domain-authority-auditor.md

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Content Refresher: Revitalizing Underperforming Content

Use this when pages are losing rankings, traffic has declined, or content has outdated statistics.

Decay indicators that trigger a refresh:

• Page ranking positions dropped ≥5 spots in last 90 days
• Organic traffic declined ≥20% year-over-year
• Content contains statistics >18 months old
• Competitors have published more recent, deeper coverage
• Broken links present (R10 violation)
• Key sections missing vs. current top-ranking pages

9-Step Refresh Workflow

Step 1 — CORE-EEAT Quick Score Run the 16-item quick scan (see Per-Page Audit section) to identify the weakest dimensions. Focus the refresh on dimensions scoring below 60.

Step 2 — Decay Candidate Identification Check content against six criteria: age, outdated data, traffic loss, ranking drops, broken links, competitive gaps. Score each 0–2; pages scoring ≥4/12 are refresh candidates.

Step 3 — Performance Analysis Document current state: keyword positions (before/now), organic traffic trend, SERP changes (new competitors, new features), search intent shift.

Step 4 — Gap Identification Compare against current top 3 ranking pages:

• Missing sections or subtopics
• Outdated statistics (flag specific claims with dates)
• Schema markup gaps
• Missing FAQ for PAA questions now appearing

Step 5 — Update Requirements List specific changes: statistics to replace, sections to add, sections to rewrite, schema to add/fix, internal links to update.

Step 6 — Content Writing Update sections with current data. Replace every statistic with a sourced, dated replacement. Add missing subtopics. Strengthen E, R dimensions (original data, citations).

Step 7 — GEO Optimization Add/improve: Direct Answer block (C02), Summary Box (O02), Data Tables (O03), FAQ section with schema (C09), entity precision throughout (R07).

Step 8 — Republishing Strategy

• Update the <lastmod> date in sitemap
• Add/update "Last updated: [date]" visible on the page
• Promote refreshed content as new via newsletter/social
• Submit updated URL in Google Search Console

Step 9 — Refresh Report Document: what changed, CORE-EEAT score before/after, expected ranking recovery timeline (typically 4–8 weeks), set 90-day review checkpoint.

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Entity Optimization

Use when a brand, author, or product is:

• Not appearing correctly in AI system responses
• Confused with a similarly-named competitor
• Missing from Knowledge Panels or Wikidata
• Losing citations because AI can't resolve the entity

Key principle: Consistency beats completeness. Five consistent weak signals across platforms are stronger than one strong signal on a single platform.

3-Step Workflow

Step 1 — Entity Discovery Check Google Knowledge Panel presence, Wikidata entry, Wikipedia page, AI system recognition (query ChatGPT/Claude: "What is [brand]?"), and schema markup on homepage.

Step 2 — Signal Audit Evaluate 6 dimensions: structured data, knowledge bases, NAP+E consistency, content authority, third-party mentions, AI-specific signals.

Step 3 — Action Plan

• Phase 1 (Week 1–2): Add Organization/Person schema with sameAs links; ensure NAP+E consistency across top 20 directories
• Phase 2 (Month 1–2): Create/claim Wikidata entry; improve Wikipedia accuracy if applicable
• Phase 3 (Month 2–4): Earn authoritative third-party mentions; build press coverage
• Phase 4 (Ongoing): Structure content with Direct Answer blocks, FAQ sections, full entity names throughout

For schema templates, disambiguation strategies, and monitoring workflows: see references/entity-optimizer.md

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Monitoring & Alerts

Proactive monitoring detects problems before they become crises. Configure alerts across seven categories:

| Category | Urgency | Trigger Examples | |----------|---------|-----------------| | Technical | Critical | Crawl errors spike, robots.txt change, site down | | Traffic | High | Organic traffic drops ≥20% week-over-week | | Rankings | High | Top keyword drops ≥5 positions | | Backlinks | Medium | Toxic link spike, significant link loss | | Competitors | Medium | Competitor publishes content on your target keywords | | GEO/AI Visibility | Medium | AI citation share drops on monitored queries | | Brand Mentions | Medium | Negative brand mentions spike |

Alert Setup Workflow

1. Define categories with urgency levels and response SLAs (Critical=same day, High=24h, Medium=next business day, Low=weekly review)
2. Configure rules with specific thresholds per alert (e.g., "notify if position drops >5 for any top-20 keyword")
3. Set response plans — what action to take when each alert fires
4. Configure channels — Email, Slack, SMS by severity level
5. Establish baseline — document current state so alerts have context

Recommended baseline metrics to track:

• Top 20 keywords: current positions, search volumes
• Weekly organic sessions (set alert at -20% week-over-week)
• Domain authority metrics (monthly)
• AI visibility: monthly manual check of top 10 queries in ChatGPT, Perplexity, Google

DIY monitoring (no tools): Monthly, pick your top 20 queries → test each in ChatGPT, Perplexity, Google → record: are you cited? Who is? Which page? → track month-over-month in a spreadsheet.

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Slash Commands Quick Reference

These one-shot commands run specific SEO/GEO tasks without entering the full audit workflow:

| Command | What It Does | |---------|-------------| | /seo:audit-page [url] | Full per-page on-page audit with CORE-EEAT quick scan (11-step workflow) | | /seo:audit-domain [domain] | Complete site audit: technical + on-page + GEO + competitor overview | | /seo:check-technical [url] | Technical SEO check: crawlability, speed, schema, mobile, security (9-step) | | /seo:write-content [topic] | Create SEO-optimized content with keyword integration, schema, and FAQ | | /seo:keyword-research [topic] | Full keyword research workflow: discovery, intent classification, opportunities | | /seo:optimize-meta [url] | Optimize title tag, meta description, OG tags, and Twitter Cards | | /seo:generate-schema [url] | Generate appropriate JSON-LD schema markup for the page | | /seo:report [domain] | Generate a performance summary report with rankings, traffic, and GEO metrics | | /seo:setup-alert [domain] | Configure monitoring alerts for rankings, traffic, and AI visibility |

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Reference Files

| File | Contents | |------|----------| | references/technical-seo.md | Deep technical audit checklist, crawl issues, JS SEO, international SEO | | references/geo-strategies.md | GEO and AEO deep strategies by AI platform and content domain | | references/geo-research.md | Princeton GEO paper (KDD 2024) — 9 optimization methods with quantified visibility boosts, domain-specific recommendations | | references/platform-algorithms.md | Per-platform ranking algorithms: ChatGPT, Perplexity, Google AI Overview, Copilot, Claude, traditional Google | | references/structured-data.md | Complete JSON-LD schema templates for every content type | | references/seo-checklist.md | Priority-tiered audit checklist (P0/P1/P2) covering technical, on-page, schema, GEO, and off-page factors | | references/content-optimization.md | Content strategy, search intent, featured snippets, internal linking | | references/tools-and-apis.md | Free/paid SEO tools, GEO monitoring tools, APIs, browser extensions, robots.txt template for AI bots | | references/nextjs-implementation.md | Next.js metadata API, sitemaps, robots.ts, dynamic OG images, i18n with react-i18next, auto-translation workflow | | references/ai-signals.md | E-E-A-T implementation, AI writing detection patterns to avoid | | references/measurement.md | SEO + GEO KPIs, tracking setup, competitive benchmarking | | references/content-patterns.md | GEO writing patterns (statistic blocks, expert quotes, evidence sandwiches), domain-specific tactics, voice search optimization | | references/on-page-audit.md | Per-page on-page audit: detailed output templates for steps 1-11, scoring rubric with calibration examples, content length benchmarks, URL quality guide, internal link count guidelines, issue resolution playbook, worked example (headphones), page-type checklists | | references/keyword-intent-taxonomy.md | Complete intent classification system: 4 primary types × 3–4 sub-categories, signal words, SERP feature correlations, content format recommendations, full funnel alignment, and mixed intent patterns | | references/keyword-prioritization-framework.md | Priority scoring matrix (5-factor weighted scoring), P0–P3 priority categories with action guidance, and seasonal keyword patterns with planning lead times | | references/topic-cluster-templates.md | Topic cluster planning worksheets, four hub-and-spoke architecture patterns, internal linking rules and anti-patterns, content calendar integration with build sequence, cluster health scorecard | | references/backlink-hunter.md | Automated broken-link backlink outreach: full agentic workflow spec, Brave Search queries, link extraction logic, LLM-powered email drafting, state management, and outreach templates | | references/core-eeat-benchmark.md | Full 80-item CORE-EEAT content quality framework: complete checklist for all 8 dimensions, content-type weight tables, GEO engine citation preferences, schema-by-content-type guide, and Pass/Partial/Fail calibration examples | | references/domain-authority-auditor.md | CITE domain authority framework: full 40-item checklist (Citation/Identity/Trust/Eminence), domain-type weight tables, veto item details, scoring workflow, and CITE × CORE-EEAT diagnosis matrix | | references/entity-optimizer.md | Entity optimization: 6 signal dimensions, 3-step audit workflow, Organization/Person schema templates, disambiguation resolution, and ongoing monitoring |

Scripts

No API Required

| File | Contents | |------|----------| | scripts/seo_audit.py | Full SEO audit — meta tags, H1, robots.txt, sitemap, AI bot access, load time, schema count. No API key needed. Run: python3 scripts/seo_audit.py "https://example.com" | | scripts/translate_i18n.py | Translates all string values in an i18n JSON locale file to one or more target languages using an AI provider. Preserves structure, keys, URLs, and {{placeholder}} variables. Run python scripts/translate_i18n.py --help for usage. |

DataForSEO API (requires DATAFORSEO_LOGIN + DATAFORSEO_PASSWORD)

| File | Contents | |------|----------| | scripts/dataforseo_api.py | API wrapper + shared utilities (format_count, get_result, print helpers) | | scripts/credential.py | Credential helper reading env vars | | scripts/keyword_research.py | Keyword ideas with search volume and difficulty: python3 scripts/keyword_research.py "seo tools" --limit 20 | | scripts/serp_analysis.py | Top Google SERP results for a keyword: python3 scripts/serp_analysis.py "best seo tools" --depth 20 | | scripts/backlinks.py | Backlink profile for a domain: python3 scripts/backlinks.py "example.com" --limit 20 | | scripts/domain_overview.py | Domain organic traffic and keyword count: python3 scripts/domain_overview.py "example.com" | | scripts/related_keywords.py | Google "searches related to" — up to 4,680 keyword ideas: python3 scripts/related_keywords.py "AI agent" --depth 2 --limit 50 | | scripts/competitor_gap.py | Keywords competitor ranks for but you don't: python3 scripts/competitor_gap.py "opc.dev" "competitor.com" | | scripts/autocomplete_ideas.py | Real-time Google Autocomplete suggestions: python3 scripts/autocomplete_ideas.py "Claude Code" |

Example Files

| File | Contents | |------|----------| | examples/nextjs-metadata.ts | Next.js generateMetadata patterns and OG configuration | | examples/schema-examples.json | Ready-to-use JSON-LD schema blocks | | examples/content-blocks.md | AEO/GEO content templates with fill-in-the-blank patterns | | examples/opc-skills-case-study.md | Real-world optimization case study — keyword research, schema implementation, Princeton methods applied | | examples/keyword-research-example-report.md | Complete example keyword research report for "project management software for small businesses" — executive summary, quick wins, growth keywords, GEO opportunities, topic clusters, content calendar |

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Follow-Up

After presenting an audit, offer:

"Would you like me to:

• Draft content briefs for the top keyword opportunities?
• Create optimized title tags and meta descriptions for your key pages?
• Build a content calendar based on the gap analysis?
• Run a broken-link backlink outreach campaign to build links to your top pages?
• Run the full 80-item CORE-EEAT audit on a specific page?
• Run the CITE domain authority audit to diagnose why content isn't being cited?
• Identify top content refresh candidates from your existing pages?
• Audit your entity presence in Google Knowledge Graph and AI systems?
• Set up a monitoring alert configuration for rankings and AI visibility?
• Dive deeper into any specific section of the audit?
• Run this same analysis for a different competitor or domain?"

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Related Skills

• Use blog-articles when the user first needs a strong canonical article before optimization.
• Use content-syndication when the optimized piece needs channel-specific variants after SEO and GEO improvements.