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By EricGrill
Audit existing content for SEO quality, E-E-A-T signals, readability, and structure with scored recommendations; plan topic clusters, outlines, and content calendars to build topical authority; generate optimized articles including titles, meta descriptions, FAQs, and key takeaways from keywords and briefs.
npx claudepluginhub ericgrill/agents-skills-plugins --plugin seo-content-creationCreates comprehensive content outlines and topic clusters for SEO. Plans content calendars and identifies topic gaps. Use PROACTIVELY for content strategy and planning.
Writes SEO-optimized content based on provided keywords and topic briefs. Creates engaging, comprehensive content following best practices. Use PROACTIVELY for content creation tasks.
Analyzes provided content for quality, E-E-A-T signals, and SEO best practices. Scores content and provides improvement recommendations based on established guidelines. Use PROACTIVELY for content review.
Uses power tools
Uses Bash, Write, or Edit tools
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Content marketing with content strategy and search specialist agents
Editorial "SEO Specialist" bundle for Claude Code from Antigravity Awesome Skills.
Content Creator subagent
Agentic SEO Skills adds project brains, data-backed SEO analysis, content workflows, and technical SEO checks to Agentic SEO.
Groups related keywords into topic clusters and creates content hub architecture recommendations with internal linking strategies. Use when planning content strategy, organizing keyword research, or building pillar page structures.
Answer Engine Optimization for AI search visibility. Optimize content for ChatGPT, Claude, Gemini, AI Overviews citations.
Automated code review for pull requests using multiple specialized agents with confidence-based scoring
Context management with save and restore capabilities
Customer support and sales automation agents
Team collaboration with DX optimization, issue tracking, and standup notes
LLM application development with RAG, embeddings, LangChain, and prompt engineering
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