claude-blog  by AgriciDaniel

AI ecosystem for scalable blog content creation and optimization

Created 1 month ago
374 stars

Top 75.9% on SourcePulse

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Project Summary

This project provides a comprehensive Claude Code skill ecosystem for creating, optimizing, and managing blog content at scale. It targets content creators, SEO specialists, and publishers seeking to enhance both search engine rankings and AI citation platform visibility, offering a streamlined workflow for high-quality, dual-optimized content.

How It Works

The system operates as a modular Claude Code skill, orchestrating 19 distinct commands and specialized agents. It employs 12 content templates, a 5-category quality scoring system (Content Quality, SEO, E-E-A-T, Technical, AI Citation Readiness), and advanced features like AI content detection, persona-driven writing, and a fact-checking pipeline. Its core advantage lies in dual optimization for Google's latest updates and AI citation platforms, ensuring content is both discoverable and quotable by AI systems.

Quick Start & Requirements

Installation is straightforward via a one-command script for Unix/macOS (curl ... | bash) or a PowerShell script for Windows (.\install.ps1). Manual installation involves cloning the repository and running install.sh. A restart of Claude Code is required post-installation. Prerequisites include the Claude Code CLI and Python 3.11+ for the quality scoring script. Optional dependencies for advanced analysis can be installed via pip install -r requirements.txt.

Highlighted Details

  • Extensive Command Suite: 19 sub-skills cover content generation, optimization, analysis, strategy, and management.
  • Content Versatility: Utilizes 12 content templates (e.g., how-to, listicle, case study, pillar page).
  • Quality & Optimization: Features a 5-category scoring system, AI content detection, persona management, fact-checking, and keyword cannibalization detection.
  • Dual Optimization: Tailored for Google rankings (Core Update, E-E-A-T) and AI citations (answer-first, passage-level citability).
  • Visual Media: Integrates AI image generation via Gemini and built-in SVG chart generation.
  • Platform Support: Compatible with Next.js/MDX, Astro, Hugo, Jekyll, WordPress, Ghost, 11ty, Gatsby, and static HTML.
  • CMS Integration: Supports taxonomy management for WordPress, Shopify, Ghost, Strapi, and Sanity.

Maintenance & Community

The project includes CONTRIBUTING.md and CHANGELOG.md files, indicating a structured approach to development and updates. No specific community channels (e.g., Discord, Slack) or notable contributors/sponsorships are detailed in the README.

Licensing & Compatibility

The project is released under the MIT License, which is permissive and generally suitable for commercial use and integration into closed-source projects without significant restrictions.

Limitations & Caveats

The primary requirement is the installation and configuration of the Claude Code CLI. Python 3.11+ is necessary for the advanced quality scoring script. AI image generation is an optional feature requiring a separate Google AI API key. The README does not detail any known bugs, alpha/beta status, or specific unsupported platforms.

Health Check
Last Commit

2 days ago

Responsiveness

Inactive

Pull Requests (30d)
5
Issues (30d)
2
Star History
260 stars in the last 30 days

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