AI Tools Collection

A comprehensive collection of AI-related tools, prompts, instructions, and documentation for personal use.

Getting Started with AI Tools

Welcome to the AI Tools collection! This guide will help you get started with using and contributing to this repository.

What’s Inside

This repository contains four main types of content:

1. Prompts: Ready-to-use AI prompts for various tasks
2. Instructions: Step-by-step guides for tools and workflows
3. Modes: AI configuration settings for different use cases
4. Thoughts: Personal insights and experimental findings

Quick Start

Using the Content

1. Browse by Category: Navigate using the main menu to find content by type
2. Search and Filter: Use the categorization system to find specific tools
3. Copy and Adapt: Most content is designed to be copied and customized
4. Learn and Iterate: Use the examples as starting points for your own tools

Local Setup (Optional)

If you want to run the site locally or contribute content:

git clone https://github.com/MauGx3/ai-tools.git
cd ai-tools
bundle install
bundle exec jekyll serve

Using Prompts

Prompts are located in the _prompts directory and organized by category:

• Coding: Development, code review, debugging
• Writing: Documentation, content creation, editing
• Analysis: Research, data analysis, evaluation
• Creative: Brainstorming, ideation, problem-solving
• Productivity: Planning, organization, optimization

Each prompt includes:

• Clear usage instructions
• Recommended AI models or settings
• Example inputs and outputs
• Variations and customization tips

Following Instructions

Instructions provide step-by-step guides for:

• Setup: Installing and configuring tools
• Usage: Operating procedures and workflows
• Best Practices: Recommended approaches and methodologies

Each instruction includes:

• Prerequisites and requirements
• Detailed step-by-step procedures
• Troubleshooting common issues
• Success criteria and validation

Configuring Modes

Modes define optimized AI interaction settings for specific use cases:

• Development: Coding and software engineering
• Research: Information gathering and analysis
• Documentation: Technical writing and communication
• Troubleshooting: Problem-solving and debugging

Each mode includes:

• Recommended AI model settings
• System prompts and configurations
• Usage guidelines and examples
• Integration tips and best practices

Understanding Thoughts

Thoughts capture personal insights, experiments, and ideas:

• Reflections: Learning insights from tool usage
• Experiments: Testing new approaches and techniques
• Ideas: Future improvements and potential projects

Each thought includes:

• Background context and motivation
• Detailed findings and analysis
• Current status and next steps
• Lessons learned and recommendations

Contributing Guidelines

Adding New Content

1. Choose the appropriate collection type
2. Create a file with descriptive naming
3. Include complete front matter metadata
4. Follow established content patterns
5. Test and validate your additions

Content Quality Standards

• Clear Purpose: Each item should have a specific, well-defined use case
• Complete Information: Include all necessary details for effective use
• Practical Examples: Provide working examples and real-world applications
• Consistent Format: Follow the established templates and structures
• Accurate Metadata: Use proper categories, tags, and descriptions

File Organization

Collection Structure:
├── _prompts/
│   └── category-specific-name.md
├── _instructions/
│   └── type-specific-procedure.md
├── _modes/
│   └── use-case-configuration.md
└── _thoughts/
    └── topic-insight-or-experiment.md

Metadata Templates

Each content type has specific front matter requirements. See the existing files for examples, or check the documentation for complete templates.

Best Practices

For Using AI Tools

1. Start with Examples: Use existing content as templates
2. Customize for Context: Adapt prompts and instructions for your specific needs
3. Iterate and Improve: Refine your approach based on results
4. Document Your Learning: Consider contributing insights back to the collection

For Contributing Content

1. Quality over Quantity: Focus on useful, well-documented content
2. Test Before Sharing: Validate that your content works as intended
3. Provide Context: Explain when and why to use specific tools
4. Maintain Currency: Keep content updated and relevant

Getting Help

If you need assistance:

1. Browse Similar Content: Look for related examples and patterns
2. Check Documentation: Review the guides and references
3. Review Existing Issues: See if your question has been addressed
4. Ask Questions: Open an issue for complex problems or suggestions

Next Steps

1. Explore the Collections: Browse through different content types
2. Try Some Examples: Use existing prompts and instructions
3. Customize for Your Needs: Adapt content for your specific use cases
4. Share Your Experience: Consider contributing your own tools and insights

Happy learning and building with AI tools!