Structured, scalable prompt engineering for modern development
This repository demonstrates the power of Context Engineering - a systematic approach to prompt design that generates complete, production-ready applications from well-structured prompts.
Context Engineering is the art and science of crafting prompts that:
- Structure information for maximum AI comprehension
- Provide clear specifications for consistent outputs
- Enable reproducible results across different AI models
- Scale from simple demos to complex applications
# Browse our generated examples
cd examples/todo-app-generated
npm install
npm run dev# Start with our React/TypeScript template
cp -r templates/react-typescript-base my-new-project# Use our context templates
cp prompts/todo-app-context.md my-prompt.md
# Edit and customize for your needsscriptonia/context-engineering-examples/
├── prompts/ # Structured prompt templates
├── examples/ # Generated application examples
├── templates/ # Reusable project bases
├── docs/ # Comprehensive documentation
└── .github/ # Community templates & workflows
- Browse Examples: See what's possible with context engineering
- Use Templates: Start new projects with proven structures
- Study Prompts: Learn from our prompt engineering techniques
- Contribute: Add your own examples and improvements
- Context Patterns: Study our prompt structures
- Output Specifications: See how we specify requirements
- Reproducibility: Use our templates for consistent results
- Best Practices: Learn from our documentation
Our flagship example demonstrates a complete React/TypeScript application generated from a single, well-structured prompt:
- Frontend: Modern React with TypeScript
- State Management: Clean, predictable state handling
- Styling: Responsive, accessible design
- Testing: Comprehensive test coverage
- Documentation: Clear setup and architecture docs
We welcome contributions! Whether you're:
- Adding new examples
- Improving existing prompts
- Creating new templates
- Enhancing documentation
See our Contributing Guide for details.
- Context Engineering Guide - Learn the fundamentals
- Roadmap - Our development plans
- Token Utility - How SCRIPT tokens enhance the ecosystem
This repository is part of the broader Scriptonia ecosystem:
- SCRIPT Token: Utility token for enhanced AI interactions
- Context Engineering: Systematic prompt design methodology
- Developer Tools: Templates, examples, and best practices
- Community: Open-source collaboration and knowledge sharing
MIT License - see LICENSE for details.
Ready to revolutionize your AI development workflow? Start with our examples and templates, then contribute your own innovations to the community!