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Contributing to Prompt Fusion

Thank you for your interest in contributing to Prompt Fusion! This project is about exploration and discovery in prompt composition for AI agents.

Ways to Contribute

1. Report Issues or Bugs

  • Use GitHub Issues to report problems
  • Provide clear reproduction steps
  • Include the fusion pattern you were using
  • Share the framework (LangChain, OpenAI SDK, etc.)

2. Suggest New Weight Patterns

Have you discovered an effective weight pattern for a specific scenario?

  • Document the pattern (weights and use case)
  • Explain why it works better than alternatives
  • Share example results if possible

3. Improve Documentation

  • Fix typos or clarify existing docs
  • Add examples or use cases
  • Translate documentation
  • Improve code comments

4. Add Framework Integration Examples

We welcome examples for additional frameworks:

  • Google Gemini
  • Cohere
  • Open source LLM frameworks
  • Other agent frameworks

Requirements:

  • Use official SDK documentation
  • Include clear, working examples
  • Follow the existing example structure
  • Add README specific to that integration

5. Share Benchmarks or Case Studies

Real-world results are valuable:

  • Performance comparisons
  • A/B test results comparing patterns
  • Production deployment experiences
  • Theoretical insights

Community Ethos

This project values:

  • Exploration - Novel applications of semantic weighting
  • Evidence - Data-driven insights about what works
  • Clarity - Clear explanations over complex abstractions
  • Openness - Sharing discoveries, even negative results

We're interested in:

  • How different LLMs respond to semantic weighting
  • Optimal weight distributions for different tasks
  • Real-world use cases and patterns
  • Theoretical insights into prompt composition

Code Contribution Guidelines

Before You Start

  1. Check existing issues - Someone may already be working on it
  2. Open a discussion - For major changes, discuss first
  3. Start small - Small PRs are easier to review

Code Style

  • Core engine - Keep it dependency-free and framework-agnostic
  • Examples - Use official SDK documentation patterns
  • Comments - Explain the "why", not just the "what"
  • Tests - Include tests for core functionality changes

Pull Request Process

  1. Fork the repository
  2. Create a feature branch 
    git checkout -b feature/your-feature-name
  3. Make your changes
    • Write clear commit messages
    • Follow existing code style
    • Add tests if applicable
  4. Test thoroughly
    • Ensure existing tests pass
    • Test your changes manually
  5. Submit PR
    • Clear description of changes
    • Reference related issues
    • Explain the reasoning

Commit Message Format

type: brief description

Detailed explanation if needed

Fixes #issue-number

Types:

  • feat: New feature
  • fix: Bug fix
  • docs: Documentation changes
  • refactor: Code refactoring
  • test: Test additions or changes
  • chore: Maintenance tasks

Example Contributions

Good:

## Add Claude extended thinking example

Adds example showing how to use Prompt Fusion with Claude's
extended thinking mode.

Based on official Anthropic documentation.

Includes:
- Working code example
- Explanation of thinking + fusion interaction
- Edge case handling

Needs improvement:

## Update

Changed some stuff

Project Structure

prompt-fusion-publication/
├── core/                    # Core fusion engine (framework-agnostic)
├── patterns/                # Reusable fusion patterns
├── examples/
│   ├── langchain/          # LangChain integration
│   ├── openai-sdk/         # OpenAI SDK integration
│   └── anthropic/          # Anthropic integration
├── docs/                   # Deep-dive documentation
└── website/                # Landing page

Where to contribute:

  • Core improvements → core/promptFusionEngine.js
  • New patterns → patterns/
  • Framework examples → examples/[framework-name]/
  • Documentation → docs/ or README.md

Questions or Ideas?

  • Issues - For bugs and feature requests
  • Discussions - For questions and ideas
  • Email - For private inquiries

Code of Conduct

Be respectful and constructive:

  • Welcome newcomers
  • Assume good intentions
  • Provide constructive feedback
  • Focus on ideas, not individuals

Recognition

Contributors will be recognized in:

  • README acknowledgments
  • Release notes
  • Project documentation

Significant contributions may lead to collaborator status.

Let's explore what's possible with semantic weighted prompt composition together.