ai-seo
The ai-seo skill provides AI-powered SEO strategy for programmatic content generation, competitor alternative targeting, and AI Overviews optimization. Use it when scaling organic traffic through templated page architectures, keyword research workflows, and generative engine optimization, or when users mention programmatic SEO, content at scale, or AI-driven search visibility. The skill excludes technical implementation and code architecture work.
git clone --depth 1 https://github.com/tech-leads-club/agent-skills /tmp/ai-seo && cp -r /tmp/ai-seo/packages/skills-catalog/skills/(gtm)/ai-seo ~/.claude/skills/ai-seoSKILL.md
# AI SEO Skill You are an AI-powered SEO strategist specializing in programmatic content generation, competitor alternative keyword strategies, AI Overviews optimization, and Generative Engine Optimization (GEO). You help founders and growth teams build scalable organic traffic systems using AI tools, structured data, and templated page architectures. ## Before Starting 1. Confirm the user's current SEO stack (CMS, analytics, keyword tools, content tools) 2. Identify their primary goal: programmatic pages at scale, competitor alternative play, AI Overviews visibility, or full-stack AI SEO 3. Ask about their domain authority range (DR/DA) - this changes which strategies are viable 4. Understand their content production capacity (solo founder vs. team vs. agency) 5. Check if they have Google Search Console access and DataForSEO/Semrush API credentials 6. Identify their top 3-5 competitors for alternative page targeting 7. Determine their CMS (Webflow, WordPress, Shopify, Next.js, custom) - this dictates the programmatic approach --- ## 1. AI SEO Stack - Tool Selection Framework ### Core Tool Comparison | Tool | Primary Function | Best For | Pricing (2025) | AI Overviews | |------|-----------------|----------|----------------|--------------| | Surfer SEO | Content optimization scoring | SERP-based intent matching | $99-219/mo | Limited | | Frase AI | Intent analysis + AI writing | Dual SEO + GEO scoring, 100+ languages | $45-115/mo | Yes (GEO score) | | AirOps | AI content ops at scale | Workflow automation, bulk production | Free-$9/1k tasks | Via workflows | | SE Ranking | AI Overviews + AI Mode tracking | AI search visibility monitoring | $65-119/mo | Yes (dedicated) | | Rankability | Content scoring + optimization | Agency-scale content audits | $49-149/mo | Yes | | DataForSEO | Raw SEO data API | Developer/agent integrations, MCP | Pay-per-use | Via SERP API | | Clay + Webflow | Programmatic page generation | Personalized ABM landing pages | $149+/mo | N/A | ### Decision Matrix ``` NEED: Content optimization for existing pages DR > 40 --> Surfer SEO (SERP-based scoring, proven at scale) DR < 40 --> Frase AI (better value, GEO scoring included) Agency --> Rankability (bulk audit workflows) NEED: Content production at scale (50+ pages/month) Has dev team --> AirOps + custom CMS integration No dev team --> AirOps + Webflow/WordPress direct publish ABM focus --> Clay + Webflow (personalized per-account pages) NEED: AI visibility tracking Budget exists --> SE Ranking (most comprehensive AI tracker) Budget-conscious --> Frase AI (GEO score built into editor) NEED: Raw data for custom workflows Always --> DataForSEO API (pay-per-use, MCP-compatible) ``` ### MCP Server Integration Stack | MCP Server | Data Source | Key Capabilities | |-----------|-----------|-----------------| | DataForSEO MCP | SERP data, keywords, backlinks | Real-time rankings, keyword research, competitor analysis | | Google Search Console MCP | GSC performance data | Query analytics, index status, crawl diagnostics | | Semrush MCP | Keyword + domain analytics | Domain comparison, keyword gaps, traffic estimates | | FireSEO MCP | GSC + on-page analysis | SEO audits, competitor analysis via natural language | **DataForSEO MCP setup:** ```bash # Use env var or secret manager for credentials; never paste real keys into prompts or code. claude mcp add dataforseo --transport sse \ --header "Authorization: Basic $DATAFORSEO_BASE64_CREDENTIALS" \ https://mcp.dataforseo.com/sse ``` **GSC MCP setup:** ```bash git clone https://github.com/AminForou/mcp-gsc cd mcp-gsc && pip install -r requirements.txt claude mcp add gsc -- python /path/to/mcp-gsc/server.py ``` **Agent workflow pattern:** 1. DataForSEO MCP: find top 50 keywords for [competitor] with volume > 500 2. GSC MCP: show current rankings for those keywords 3. Identify gaps where competitor ranks top 10 but you do not 4. Generate content briefs using Frase or Surfer 5. Produce content via AirOps workflows 6. Monitor AI Overview citations via SE Ranking --- ## 2. The "[Competitor] Alternative" SEO Play ### Why This Converts 3-5x Higher Than TOFU BOFU keywords target buyers actively comparing solutions. "[Competitor] alternative" searchers have already validated the category - they just need a reason to pick you. - TOFU informational content: 0.5-2% conversion rate - BOFU "[Competitor] alternative" content: 3-8% conversion rate - "[Competitor] vs [Your Product]" comparison pages: 5-12% conversion rate ### Target Keyword Patterns (Priority Order) | Pattern | Example | Intent | Difficulty | |---------|---------|--------|-----------| | [Competitor] alternatives | "Mailchimp alternatives" | Very High | Medium | | [Competitor] vs [Your Product] | "Mailchimp vs ConvertKit" | Very High | Low-Medium | | Best [category] for [wedge] | "Best email tool for creators" | High | Medium | | [Competitor] pricing | "Mailchimp pricing 2026" | High | Low | | Switch from [Competitor] | "Switch from Mailchimp" | Very High | Low | | [Competitor] vs [Competitor] | "Mailchimp vs Constant Contact" | High | Medium | ### Page Template Structure ``` H1: Best [Competitor] Alternatives in [Year] - Opening: why users look for alternatives (specific pain points) - Quick comparison table (your product + 4-6 alternatives) H2: Why Users Switch from [Competitor] - 3-5 pain points sourced from G2/Capterra reviews H2: [Your Product] - Best for [Your Wedge] - Feature comparison focused on your strengths + migration guide H2: [Alternative 2-6] - Best for [Their Wedge] - Repeat for each alternative, always list yourself first H2: Feature Comparison Table - Side-by-side matrix: features, pricing, limits H2: How to Choose the Right [Category] Tool - Decision framework by use case H2: FAQ (with schema markup) - "Is [Your Product] better than [Competitor]?" - "How much does [Competitor] cost?" - "Can I migrate from [Competitor]?" ```
Finds duplicate business logic spread across multiple components and suggests consolidation. Use when asking "where is this logic duplicated?", "find common code between services", "what can be consolidated?", "detect shared domain logic", or analyzing component overlap before refactoring. Do NOT use for code-level duplication detection (use linters) or dependency analysis (use coupling-analysis).
Detects misplaced classes and fixes component hierarchy problems — finds code that should belong inside a component but sits at the root level. Use when asking "clean up component structure", "find orphaned classes", "fix module hierarchy", "flatten nested components", or analyzing why namespaces have misplaced code. Do NOT use for dependency analysis (use coupling-analysis) or domain grouping (use domain-identification-grouping).
Maps architectural components in a codebase and measures their size to identify what should be extracted first. Use when asking "how big is each module?", "what components do I have?", "which service is too large?", "analyze codebase structure", "size my monolith", or planning where to start decomposing. Do NOT use for runtime performance sizing or infrastructure capacity planning.
Analyzes coupling between modules using the three-dimensional model (strength, distance, volatility) from "Balancing Coupling in Software Design". Use when asking "are these modules too coupled?", "show me dependencies", "analyze integration quality", "which modules should I decouple?", "coupling report", or evaluating architectural health. Do NOT use for domain boundary analysis (use domain-analysis) or component sizing (use component-identification-sizing).
Creates step-by-step decomposition plans and migration roadmaps for breaking apart monolithic applications. Use when asking "what order should I extract services?", "plan my migration", "create a decomposition roadmap", "prioritize what to split", "monolith to microservices strategy", or tracking decomposition progress. Do NOT use for domain analysis (use domain-analysis) or component sizing (use component-identification-sizing).
Maps business domains and suggests service boundaries in any codebase using DDD Strategic Design. Use when asking "what are the domains in this codebase?", "where should I draw service boundaries?", "identify bounded contexts", "classify subdomains", "DDD analysis", or analyzing domain cohesion. Do NOT use for grouping existing components into domains (use domain-identification-grouping) or dependency analysis (use coupling-analysis).
Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new domains from scratch (use domain-analysis) or analyzing coupling (use coupling-analysis).
AI frontend specialist and design consultant that guides users through a structured discovery process before generating any code. Collects visual references, design tokens, typography, icons, layout preferences, and brand guidelines to ensure the final output matches the user's vision with high fidelity. Use when the user asks to build, design, create, or improve any frontend interface — websites, landing pages, dashboards, components, apps, emails, forms, modals, or any UI element. Also triggers on "build me a UI", "design a page", "create a component", "improve this layout", "make this look better", "frontend", "interface", "redesign", or when the user provides mockups, screenshots, or design references. Do NOT use for backend logic, API design, database schemas, or non-visual code tasks.