SEO Skill

Comprehensive SEO optimization covering three pillars: 1. Traditional SEO - Google/Bing (mid-funnel focus) 2. Answer Engine Optimization (AEO) - ChatGPT, Perplexity, AI Overviews 3. Agent & LLM Accessibility - llms.txt, structured data, semantic HTML

Core Concept: The New SEO Landscape

Traditional SEO focused on ranking #1 to win clicks. With AI Overviews and LLM-powered search, the game has changed:

Key insight: Mid-funnel intent is where SEO opportunity remains. AI handles discovery; SEO handles intent.

Workflow Overview

Execute these 8 phases: 1. Discovery & Fit Assessment - Is SEO right for this product? 2. Site/Content Analysis - Current state assessment 3. Traditional SEO Assessment - Mid-funnel optimization 4. Answer Engine Optimization - AEO strategy 5. Citation Strategy - Multi-platform citation plan 6. Agent & LLM Accessibility - Technical accessibility 7. Implementation/Creation - Execute recommendations 8. Monitoring & Measurement - Track share of voice

Phase 1: Discovery & Fit Assessment

Goal: Determine if SEO is right for this product and select workflow mode.

Mode Selection

Audit Mode - Analyzing existing site/content: - User provides URL or content - Output: Recommendations, issues, implementation guide

Creation Mode - Generating optimized content: - User provides topic, keywords, or brief - Output: SEO-optimized content with all assets

Critical Fit Assessment

Before proceeding, assess if SEO makes sense:

SEO is likely a good fit if: - Clear search journey exists (users search to find this) - Users convert online (not requiring sales team) - Mid-funnel intent keywords exist - Product solves a searchable problem

SEO may NOT be right if: - No clear answer to "what will someone search to find this?" - B2B SaaS with long sales cycles/committee decisions - Products requiring sales motion to convert - No online conversion path

Read: references/traditional-seo.md for "When NOT to do SEO" framework.

Initial Context

Gather: - Target URL or topic - Primary goals (traffic, citations, conversions) - Target audience - Competitive context - Funnel position (top/mid/bottom)

Phase 2: Site/Content Analysis

Goal: Deep understanding of current state.

For Audit Mode

1. Fetch and analyze target URL: - Use WebFetch to retrieve page content - Examine HTML structure, meta tags, headers - Check for structured data presence

2. Content inventory: - Main topics and themes - Content structure and hierarchy - Internal linking patterns

3. Citation presence check: - Search ChatGPT/Perplexity for relevant queries - Note which competitors are being cited - Identify citation gaps

For Creation Mode

1. Research target topic: - Use WebSearch to understand landscape - Analyze top-ranking and top-cited content - Identify content gaps

2. Question research: - Transform keywords → questions - Identify follow-up questions users ask - Map the full question cluster

Read: references/analysis-checklists.md for detailed procedures.

Phase 3: Traditional SEO Assessment (Mid-Funnel Focus)

Goal: Optimize for Google/Bing mid-funnel searches.

Read: references/traditional-seo.md for detailed guidance.

On-Page Elements

Title Tags

• 50-60 characters
• Primary keyword near beginning
• Unique, compelling, accurate

Meta Descriptions

• 150-160 characters
• Include call-to-action
• Reflect page content accurately

Header Structure

• Single H1 per page
• Logical H2-H6 hierarchy
• Keywords in headers (natural, not stuffed)

Content Quality

E-E-A-T Signals

• Experience: First-hand knowledge demonstrated
• Expertise: Credentials and depth shown
• Authoritativeness: Recognition from others
• Trustworthiness: Accuracy, transparency

Follow-Up Question Coverage

Critical for both SEO and AEO: Answer ALL subtopics and follow-up questions. - Mine questions from sales calls, customer support - Cover edge cases and specific use cases - Structure content to address question clusters

Help Center Optimization

Underrated SEO opportunity: - Move help center from subdomain → subdirectory - Cross-link help center pages - Fill long-tail from support tickets - Open to community for obscure questions

Phase 4: Answer Engine Optimization (AEO)

Goal: Optimize for ChatGPT, Perplexity, AI Overviews citations.

Read: references/answer-engine-optimization.md for detailed methodology.

Core AEO Concept

LLMs use RAG (Retrieval Augmented Generation) - they search, then summarize. Your goal: be mentioned in as many citations as possible.

Question Research

Transform keywords → questions: 1. Take money keywords (yours and competitors' paid search) 2. Convert to question format 3. Include follow-up question variants

Example: "CRM software" → - "What is the best CRM for small businesses?" - "Which CRM integrates with Gmail?" - "How much does CRM software cost?"

Answer-Optimized Content

Structure content for citation: - Lead with direct answers (first sentence should answer the query) - Use clear, quotable statements - Include unique data and statistics - Demonstrate expertise with credentials

Platform Considerations

Phase 5: Citation Strategy

Goal: Build presence across all citation sources.

Read: references/citation-strategies.md for platform-specific tactics.

Citation Groups Framework

1. Your Site

• Traditional SEO landing pages
• Help center content
• FAQ pages with question-answer format

2. Video (YouTube/Vimeo)

• Huge B2B opportunity (few videos on technical topics)
• No community gatekeeping like Reddit
• Target high-LTV, non-glamorous keywords
• Example: "AI payment processing API tutorial"

3. UGC (Reddit, Quora)

Reddit Strategy (most important): - Spam does NOT work - fake accounts banned - Winning approach: - Real account with history - Say who you are and where you work - Give genuinely useful answers - Even 5 good comments can help

Quora Strategy: - Answer questions with expertise - Link to resources where relevant - Build topic authority

4. Tier 1 Affiliates

• Dot Dash Meredith (Good Housekeeping, Investopedia, etc.)
• G2, Capterra, TrustRadius
• Industry publications

5. Tier 2 Affiliates & Blogs

• Niche blogs in your space
• Guest posting (authentic, not spam)
• PR mentions

Phase 6: Agent & LLM Accessibility

Goal: Make content machine-readable for AI agents.

Read: references/agent-accessibility.md for detailed guidance.

llms.txt

A machine-readable file helping LLMs understand site structure.

Location: /llms.txt at site root

Contents: - Site purpose and scope - Key pages and purposes - Content organization - API/data access points - Contact/attribution

Run: scripts/generate_llms_txt.py to create template.

Structured Data (Schema.org)

Priority schemas by content type:

Run: scripts/generate_schema.py to create JSON-LD.

Semantic HTML

• Proper heading hierarchy (H1 → H2 → H3)
• Semantic elements (<article>, <section>, <nav>)
• ARIA labels for accessibility
• Clear document outline

Phase 7: Implementation/Creation

Goal: Execute optimization or generate content.

Audit Mode: Prioritized Recommendations

Structure by priority: 1. Critical: Issues blocking discoverability 2. High: Significant impact improvements 3. Medium: Moderate impact optimizations 4. Low: Nice-to-have enhancements

For each recommendation include: - What to change - Why it matters - How to implement (code snippet) - Expected impact

Creation Mode: Complete Package

Produce: 1. Main content: SEO and AEO optimized 2. Meta tags: Title, description, OG tags 3. Structured data: JSON-LD schema 4. llms.txt entry: If site-level content

Use templates: assets/templates/ for consistent formatting.

Phase 8: Monitoring & Measurement

Goal: Track success and iterate.

Read: references/monitoring-measurement.md for detailed methodology.

Key Metrics

Share of Voice

• % of prompts where domain is cited
• Track across ChatGPT, Perplexity, Gemini

Answer Tracking

• Different from keyword tracking (answers vary per run)
• Track average rank and appearance frequency
• Monitor multiple question variants

Referral Traffic

• LLM traffic sources in analytics
• Conversion rates by source

Experiment Framework

For citation strategies: 1. Select 100+ questions 2. Split into test (50) and control (50) groups 3. Intervene on test group only 4. Wait 2-4 weeks 5. Compare results 6. Reproduce successful experiments

Weekly Monitoring

• Panel of 50-100 high-intent queries
• Log which domains are cited
• Track week-over-week changes

Deliverable Generation

Read: references/output-template.md for full templates.

Audit Deliverable

# SEO Audit: [Site/Page Name]

## Executive Summary
## Fit Assessment
## Traditional SEO Findings
## AEO Findings
## Citation Strategy
## Agent Accessibility
## Prioritized Recommendations
## Implementation Checklist
## Monitoring Plan

Creation Deliverable

# SEO Content Package: [Topic]

## Optimized Content
[Main content]

## SEO Assets
- Meta tags
- Structured data (JSON-LD)
- llms.txt entry

## Citation Strategy
## Implementation Notes
## Success Metrics

Quick Reference

Conversion Benchmark

Webflow: 6X higher conversion from LLM traffic vs Google search

Citation Overlap

• ChatGPT ↔ Google: ~35%
• Perplexity ↔ Google: ~70%

Content Freshness

Visibility drops 2-3 days post-publication (for timely topics)

Reddit Rule

Even 5 authentic, useful comments > 10,000 spam comments

Scripts Reference