title	AI Tools Collection
description	A comprehensive, organized repository of AI-related tools, prompts, instructions, modes, and documentation for personal and professional use.

AI Tools Collection

A comprehensive, organized repository of AI-related tools, prompts, instructions, modes, and documentation for personal and professional use. This repository features a modern Jekyll-based documentation system that automatically deploys to GitHub Pages.

🚀 Features

• Organized Structure: Content categorized by type and purpose for easy navigation
• GitHub Pages Ready: Automatic deployment with modern, responsive design
• Comprehensive Templates: Standardized formats for prompts, instructions, modes, and thoughts
• Search & Discovery: Well-structured metadata and navigation for finding content
• Modular Design: Easy to extend and customize for specific needs
• Automation Tools: Scripts for AI-powered workflows like starred repository analysis

📁 Repository Structure

ai-tools/
├── prompts/          # AI prompts organized by category
│   ├── coding/       # Development and code review prompts
│   ├── writing/      # Content creation and documentation prompts
│   ├── analysis/     # Data analysis and research prompts
│   ├── creative/     # Brainstorming and ideation prompts
│   └── productivity/ # Planning and optimization prompts
├── instructions/     # Step-by-step guides and procedures
│   ├── setup/        # Installation and configuration guides
│   ├── usage/        # How-to guides and workflows
│   └── best-practices/ # Recommended approaches
├── modes/           # AI interaction configurations
│   ├── development/  # Coding and software development modes
│   ├── research/     # Information gathering configurations
│   ├── documentation/ # Technical writing modes
│   └── troubleshooting/ # Problem-solving configurations
├── docs/            # Comprehensive documentation
│   ├── guides/       # Detailed tutorials
│   ├── references/   # Quick reference materials
│   └── examples/     # Sample implementations
├── scripts/         # Automation scripts for AI workflows
│   └── scan_starred_repos.py  # GitHub starred repository scanner
├── data/            # Output from automation scripts (git-ignored)
│   └── example-starred-repos-analysis.md  # Example workflow output
└── thoughts/        # Personal insights and experiments
    ├── reflections/  # Learning insights and observations
    ├── experiments/  # Testing results and findings
    └── ideas/        # Future projects and improvements

🎯 Content Types

Prompts

Curated AI prompts with detailed metadata including:

• Purpose and use cases
• Category and tags for organization
• Usage examples and variations
• Best practices and tips

Instructions

Step-by-step guides covering:

• Setup and configuration procedures
• Usage workflows and best practices
• Troubleshooting common issues
• Integration with existing tools

Modes

AI interaction configurations featuring:

• Optimized system prompts
• Recommended model settings
• Use case specifications
• Integration guidelines

Thoughts

Personal reflections and experiments including:

• Learning insights and observations
• Experimental results and findings
• Future ideas and project plans
• Tool evaluation and comparisons

🤖 Automation Tools

Starred Repository Scanner

Automatically scan and analyze your GitHub starred repositories using AI:

Features:

• Fetch all starred repositories via GitHub API
• Extract comprehensive metadata (language, topics, stars, etc.)
• Generate AI-powered descriptions and use cases
• Organize repositories by category and keywords
• Export structured data for easy searching

Quick Start:

# Install dependencies
pip install requests

# Scan your starred repos
export GITHUB_TOKEN="your_token"
python scripts/scan_starred_repos.py --output data/starred-repos.json

# Analyze with AI using the Repository Analyzer prompt
# See instructions/starred-repository-scanner.md for details

Learn More:

• Getting Started Guide - 5-minute quick start
• Repository Analyzer Prompt - AI prompt for analysis
• Full Instructions - Complete setup guide
• Example Analysis - Workflow demonstration
• Implementation Notes - Design decisions

🌐 GitHub Pages Site

This repository automatically deploys to GitHub Pages, providing:

• Modern, responsive design
• Automatic navigation generation
• Search and filter capabilities
• Mobile-friendly interface
• SEO optimization

Visit the live site: https://maugx3.github.io/ai-tools

🛠️ Local Development

To run the site locally:

# Clone the repository
git clone https://github.com/MauGx3/ai-tools.git
cd ai-tools

# Install dependencies
bundle install

# Start the development server
bundle exec jekyll serve

# Visit http://localhost:4000

📝 Contributing

Adding New Content

1. Choose the appropriate collection (_prompts, _instructions, _modes, or _thoughts)
2. Create a new markdown file using the established naming convention
3. Include proper front matter with all required metadata fields
4. Follow the content structure established in existing examples
5. Test locally before committing changes

Commit Convention

This project follows Conventional Commits specification:

• feat: New features
• fix: Bug fixes
• docs: Documentation changes
• style: Code style changes (formatting, etc.)
• refactor: Code refactoring
• test: Adding or updating tests
• chore: Maintenance tasks

Example: feat(prompts): add code review prompt

The changelog is automatically generated from these conventional commits.

Content Standards

• Descriptive titles that clearly indicate purpose
• Complete metadata including categories, tags, and descriptions
• Practical examples demonstrating usage
• Clear documentation explaining when and how to use
• Consistent formatting following established patterns

📚 Documentation

For detailed documentation, including:

• Getting started guides
• Content creation templates
• Best practices and workflows
• Technical implementation details

Visit the Documentation section or the live site.

Quick links to new Diátaxis pages:

• Tutorial (Getting started): docs/tutorials/getting-started.md
• How‑to (Add a prompt or instruction): docs/how-to/add-a-prompt-or-instruction.md
• Reference (Repo structure): docs/reference/repo-structure.md
• Explanation (Design & Memory Bank): docs/explain/design-and-memory-bank.md

Contribution guidance: see CONTRIBUTING.md for workflow and Conventional Commits.

📋 Changelog

See CHANGELOG.md for a history of changes to this project.

📄 License

This project is licensed under the Mozilla Public License 2.0 - see the LICENSE file for details.

🤝 Support

For questions, suggestions, or contributions:

• Browse existing content for examples and patterns
• Check the documentation for detailed guides
• Review the issue tracker for known items
• Follow the established content standards when contributing

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Organized AI tools for enhanced productivity and learning.