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🎯 What is the Zero-AI-Trace Framework?

The Zero-AI-Trace Framework is a set of strict guidelines that transforms how LLMs (Large Language Models) generate content. It targets three main objectives:

1. 🔍 Transparency: Force verification and labeling of uncertain content
2. 🚫 Authenticity: Eliminate typically AI-sounding formulations
3. 💫 Naturalness: Inject rhythm and human imperfections

✨ Key Features

• ✅ Mandatory verification of uncertain content with labeling system
• 🎭 Automatic humanization of writing style
• 🔒 Anti-detection techniques by breaking AI patterns
• 🛠️ Integrated correction protocols automatic self-correction
• 📦 Compact format optimized for system injection
• 🔧 Universal compatibility with all major LLMs
• 🧪 Automated testing and continuous validation
• 🚀 Professional CLI interface with 6 commands
• 📚 Comprehensive documentation and detailed guides

🎬 Quick Example

❌ Without the framework:

I highly recommend using this approach as it significantly improves performance in all possible contexts.

✅ With the framework:

[Inference] This approach seems to work well from what I observe, but it totally depends on your specific context.

📊 Project Statistics

• Current Version: 1.0.1
• Automated Tests: 13/13 passing
• CLI Commands: 6 available
• Prompt Variants: 6 automatically generated
• Integration Templates: 3+ supported platforms

🤝 Community

• 💬 GitHub Discussions
• 🐛 Report a Bug
• ⭐ Star the Project