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Contributing to LLM Prompts Library 🤝

Thank you for your interest in contributing to the LLM Prompts Library! This document provides guidelines for contributing to this project.

🎯 How to Contribute

1. 🐛 Report Issues

  • Use the GitHub Issues page
  • Provide clear descriptions of problems or suggestions
  • Include examples where applicable

2. 💡 Suggest New Prompts

  • Open an issue with the "prompt suggestion" tag
  • Describe the use case and target audience
  • Explain why this prompt would be valuable

3. 🔧 Submit Pull Requests

  • Fork the repository
  • Create a feature branch: git checkout -b feature/new-prompt-name
  • Follow the prompt structure guidelines below
  • Submit a pull request with clear description

📋 Prompt Structure Guidelines

File Naming Convention

prompts/[category]-[specific-name].md

Examples:

  • prompts/code-review-assistant.md
  • prompts/blog-post-creator.md
  • prompts/documentation-generator.md

Required Prompt Structure

# 🎯 [Prompt Name]

## 📋 Prompt Overview
**Purpose:** [Clear one-sentence description]
**Best Used With:** [AI platforms/tools]
**Difficulty:** [Beginner/Intermediate/Advanced]
**Time Required:** [Estimated time]

---

## 🎯 Master Prompt

[The actual prompt content - copy-pasteable]

---

## 📚 Usage Instructions
1. [Step by step instructions]
2. [How to customize]
3. [Expected outputs]

---

## 🎨 Example Interaction
[Show expected input/output examples]

---

## 🔧 Customization Tips
[How users can adapt the prompt]

---

**Created by:** [Your name and GitHub link]
**Part of:** [LLM Prompts Collection](https://github.com/aymanaboghonim/llm-prompts)
**License:** MIT

✅ Quality Standards

Content Requirements

  • ✅ Clear purpose and target audience
  • ✅ Tested functionality with multiple AI models
  • ✅ Professional language and tone
  • ✅ Complete documentation and examples
  • ✅ Proper categorization and tags

Technical Requirements

  • ✅ Markdown formatting for consistency
  • ✅ No hardcoded personal information (use placeholders)
  • ✅ Cross-platform compatibility (works with various AI tools)
  • ✅ Error handling considerations included

🎨 Categories

Current categories (add new ones as needed):

  • 👨‍💻 Developer Tools - GitHub profiles, code review, documentation
  • 📝 Content Creation - Blog posts, social media, marketing copy
  • 🔍 Analysis & Research - Data analysis, report generation, summaries
  • 📈 Project Management - Planning, tracking, reporting
  • 🎓 Education & Training - Learning materials, tutorials, explanations

🔄 Review Process

  1. Initial Review - Maintainer checks basic requirements
  2. Testing Phase - Community testing with different AI models
  3. Feedback Integration - Incorporate suggestions and improvements
  4. Final Approval - Merge into main branch

📞 Getting Help

🎉 Recognition

Contributors will be:

  • ✅ Listed in the repository contributors
  • ✅ Credited in their prompt files
  • ✅ Featured in release notes
  • ✅ Thanked publicly on social media (if desired)

📄 Code of Conduct

Please maintain a professional, respectful, and inclusive environment:

  • ✅ Be respectful of different perspectives and experience levels
  • ✅ Provide constructive feedback and suggestions
  • ✅ Focus on the content rather than personal preferences
  • ✅ Help newcomers learn and contribute effectively

Thank you for helping make AI more accessible and effective for everyone! 🚀