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ContextX

ContextX Logo

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From Documents to Code - Let AI Understand Your Complete Intent

Context engineering framework based on Claude Code that intelligently analyzes project complexity and automatically selects the most suitable development workflow.

Core Advantages: One-Click Project Generation • Context-Aware • Zero-Config Startup

English | 简体中文

📖 Project Overview

What is this?

ContextX is a context engineering framework powered by Claude Code that automatically generates complete code projects from your documents and requirement descriptions.

What problems does it solve?

  • Requirement Communication Difficulties: AI struggles to understand complete context of complex projects
  • Low Development Efficiency: Repetitive project setup and configuration work
  • Unstable Quality: Lack of standardized AI-assisted development processes

Use Cases

  • 🚀 Rapid prototype development
  • 📚 Document-based project implementation
  • 🔄 Automated generation of repetitive projects
  • 🧠 AI-assisted development of complex business logic

⚡ Quick Start

Prerequisites

3-Step Setup

Step 1: Get the Framework

git clone https://github.com/yzfly/ContextX.git
cd ContextX

Step 2: Prepare Project Context

# Prepare your project materials in the .contextx directory
.contextx/
├── TASK_PROMPT.md          # Project requirements description
├── data/                   # Related documentation
└── examples/               # Reference code (optional)

Step 3: Generate Project

# Claude Code will automatically analyze complexity and choose the right workflow
claude "/create Your project requirements description"

First Project Example

Create a simple Todo application:

# 1. Prepare requirements description
echo "Create a React Todo app with add, delete, and mark complete functionality" > .contextx/TASK_PROMPT.md

# 2. Run generation command
claude "/create React-based Todo application"

# 3. View generated results
ls -la  # Check generated project files

💡 Core Concepts

Context-Driven Development

AI programming paradigm driven by Markdown documents, where documents serve as the project's knowledge base and context source.

Philosophy: We used to program with code, now we program with documents

Intelligent Complexity Analysis

System automatically analyzes task complexity and selects the most suitable agent workflow:

Simple Tasks  →  Builder Agent (Direct Build)
Medium Tasks  →  Designer → Builder (Design then Build)  
Complex Tasks →  Learner → Designer → Builder (Learn-Design-Build)

Agent Collaboration Model

Agent Responsibility Trigger Condition
Learner Learn and organize external docs, analyze technical specs Need to understand complex docs or new technologies
Designer Requirements analysis, architecture design, solution planning Need system design and technology selection
Builder Code implementation, documentation, deployment config Required for all projects

📚 Usage Guide

Project Preparation

1. Context Directory Structure

.contextx/
├── TASK_PROMPT.md          # [Required] Project requirements description
├── data/                   # [Optional] Related documentation
│   ├── api_docs.md         # API documentation
│   ├── business_rules.md   # Business rules
│   └── web_docs.md         # Web links (auto-fetch)
├── examples/               # [Optional] Reference code
│   ├── template.js         # Code templates
│   └── reference.py        # Reference implementations
├── knowledge/              # [Auto-generated] Structured knowledge base
└── PRC.md                  # [Auto-generated] Project requirements document

2. TASK_PROMPT.md Writing Guide

Basic Template:

# Project Requirements

## Project Overview
[One-sentence description of project goal]

## Functional Requirements
- [ ] Feature 1
- [ ] Feature 2

## Technical Requirements
- Programming Language:
- Framework Choice:
- Database: (if needed)

## Special Requirements
[Any special implementation requirements or constraints]

Advanced Template (Complex Projects):

# Project Requirements

## Background
[Project background and business value]

## User Stories
- As a [user role], I want [feature description], so that [business value]

## Functional Requirements
### Core Features
- [ ] Detailed feature description 1
- [ ] Detailed feature description 2

### Extended Features
- [ ] Optional feature 1

## Non-Functional Requirements
- Performance Requirements:
- Security Requirements:
- Maintainability:

## Technical Architecture
- Frontend Tech Stack:
- Backend Tech Stack:
- Data Storage:
- Deployment Method:

## Constraints
[Technical constraints, time constraints, etc.]

Configuration Instructions

Tool Integration (Optional)

To enhance network search capabilities, install:

# 1. Install context-mcp-server
claude mcp add context-mcp-server -e CONTEXT_DIR=$(pwd)/context/knowledge -- uvx context-mcp-server

# 2. Verify installation
claude mcp list

Web Document Retrieval

Add web links to fetch in data/web_docs.md:

# Web Document Links

## API Documentation
- https://docs.example.com/api/v1
- https://developer.example.com/guides

## Technical References
- https://framework.example.com/docs

Best Practices

✅ Recommended Practices

  • Be specific and clear in requirement descriptions, avoid vague statements
  • Provide relevant technical documentation and API specifications
  • Include specific functional examples or use cases
  • Clearly specify tech stack and architecture preferences

❌ Things to Avoid

  • Requirements that are too simple or too complex
  • Lack of key technical constraint explanations
  • Insufficient contextual information
  • Frequent requirement changes causing context inconsistency

🏗️ Architecture Design

System Architecture Diagram

                    ┌───────────────────────────────┐
                    │        /create Entry          │
                    │   Intelligent Complexity      │
                    │        Analysis               │
                    └──────────────┬────────────────┘
                                   │
            ┌──────────────────────┼──────────────────────┐
            │                      │                      │
            ▼                      ▼                      ▼
    ┌───────────────┐      ┌───────────────┐      ┌───────────────┐
    │ Simple Tasks  │      │ Medium Tasks  │      │ Complex Tasks │
    │               │      │               │      │               │
    │   Builder     │      │  Designer     │      │   Learner     │
    │               │      │     ↓         │      │     ↓         │
    │               │      │  Builder      │      │  Designer     │
    │               │      │               │      │     ↓         │
    │               │      │               │      │  Builder      │
    └───────┬───────┘      └───────┬───────┘      └───────┬───────┘
            │                      │                      │
            └──────────────────────┼──────────────────────┘
                                   │
                                   ▼
                    ┌───────────────────────────────┐
                    │    Complete Project Delivery  │
                    │ • Fully functional source code│
                    │ • Detailed project docs       │
                    │ • Deployment configuration    │
                    │ • Usage instructions          │
                    └───────────────────────────────┘

Detailed Agent Design

Learner Agent

Responsibility: Knowledge organization and learning

  • Parse external documents and technical specifications
  • Process web resources and API documentation
  • Generate structured knowledge base
  • Provide accurate technical background for subsequent agents

Input: Raw documents, web links, technical materials Output: Structured documents in .contextx/knowledge/ directory

Designer Agent

Responsibility: Requirements analysis and architecture design

  • Analyze project requirements and technical specifications
  • Design system architecture and module structure
  • Formulate technology selection and implementation plans
  • Generate detailed project requirements document (PRC.md)

Input: Task requirements, knowledge base, technical constraints Output: .contextx/PRC.md project requirements document

Builder Agent

Responsibility: Code implementation and project delivery

  • Write complete code based on requirements and design
  • Implement all functional modules and interfaces
  • Generate configuration files and deployment scripts
  • Write project documentation and usage instructions

Input: Project requirements document, design plan, code examples Output: Complete project code and documentation

Decision Flow

User Input Requirements
    │
    ▼
┌─────────────────┐
│ Requirements    │ ── Generate/optimize TASK_PROMPT.md
│ Preprocessing   │
└─────┬───────────┘
      │
      ▼
┌─────────────────┐
│ Context Resource│ ── Check data/, examples/ directories
│ Scanning        │
└─────┬───────────┘
      │
      ▼
┌─────────────────┐     ┌─────────────────┐
│ Intelligent     │ ──→ │ Simple: Direct  │
│ Complexity      │     │ Build           │
│ Assessment      │     └─────────────────┘
│                 │     ┌─────────────────┐
│ Assessment      │ ──→ │ Medium: Design  │
│ Dimensions:     │     │ + Build         │
│ • Requirement   │     └─────────────────┘
│   Clarity       │     ┌─────────────────┐
│ • Technical     │ ──→ │ Complex: Full   │
│   Difficulty    │     │ Process         │
│ • External      │     └─────────────────┘
│   Dependencies  │
│ • Material      │
│   Completeness  │
└─────────────────┘

⚙️ Advanced Configuration

Custom Agents

Create custom agents in the .claude/agents/ directory:

# custom_agent.md

## Role Definition
[Description of agent's responsibilities and capabilities]

## Workflow
[Detailed work steps]

## Input/Output
- Input: [Expected input format]
- Output: [Output format and content]

Extension Commands

Add custom commands in the .claude/commands/ directory:

# custom_command.md

## Command Description
/custom - Custom functionality description

## Usage
[Specific usage of the command]

## Parameter Description
[Detailed parameter explanations]

Configuration File

Edit .claude/settings.local.json for personalized configuration:

{
  "default_model": "claude-3-5-sonnet-20241022",
  "context_window": 200000,
  "temperature": 0.7,
  "custom_settings": {
    "preferred_language": "en-US",
    "code_style": "standard",
    "documentation_level": "detailed"
  }
}

📖 Usage Examples

Example 1: Web Application Development

# 1. Prepare requirements
cat > .contextx/TASK_PROMPT.md << EOF
# Blog Management System

## Project Overview
Create a simple blog management system supporting CRUD operations for articles.

## Functional Requirements
- [ ] User registration and login
- [ ] Article list display
- [ ] Article detail view
- [ ] Article editing and publishing
- [ ] Article deletion

## Technical Requirements
- Frontend: React + TypeScript
- Backend: Node.js + Express
- Database: SQLite
- Styling: Tailwind CSS
EOF

# 2. Run generation
claude "/create Blog management system development"

Example 2: API Integration Project

# 1. Prepare API documentation
mkdir -p .contextx/data
cat > .contextx/data/api_docs.md << EOF
# Third-party API Documentation

## User API
- GET /api/users - Get user list
- POST /api/users - Create user
- PUT /api/users/:id - Update user
- DELETE /api/users/:id - Delete user

## Authentication
Bearer Token authentication
EOF

# 2. Prepare requirements
cat > .contextx/TASK_PROMPT.md << EOF
# User Management Client

Based on the provided API documentation, create a user management frontend application.
Need to implement complete CRUD operations with user-friendly interface.
EOF

# 3. Run generation
claude "/create User management client development"

❓ FAQ

Q: How to improve the quality of generated code?

A:

  • Provide detailed requirement descriptions and technical constraints
  • Include relevant API documentation and business rules
  • Provide code examples and reference implementations
  • Clearly specify tech stack and architecture preferences

Q: What if the generated project doesn't meet expectations?

A:

  • Check if .contextx/TASK_PROMPT.md is clearly described
  • Add necessary technical documentation to the data/ directory
  • You can iteratively optimize by appending requirements
  • Review the generated PRC.md to see if the system understands correctly

Q: How to handle complex business logic?

A:

  • Break complex logic into multiple clear functional points
  • Provide business flow charts or state diagrams
  • Include specific business rule documentation
  • Provide code examples of similar business scenarios

🤝 Contributing

We welcome all forms of contributions!

How to Contribute

  1. Fork the project and create a feature branch
  2. Write code and necessary tests
  3. Update documentation to keep it in sync with code
  4. Submit PR and describe your changes

Development Workflow

# 1. Clone your fork
git clone https://github.com/your-username/ContextX.git
cd ContextX

# 2. Create feature branch
git checkout -b feature/your-feature-name

# 3. Develop
# ... your code changes

# 4. Commit changes
git add .
git commit -m "feat: add your feature description"

# 5. Push branch
git push origin feature/your-feature-name

# 6. Create Pull Request

Contribution Types

  • 🐛 Bug Fixes: Fix known issues
  • New Features: Add new functionality
  • 📚 Documentation Improvements: Enhance docs and examples
  • 🔧 Tool Optimization: Improve development tools and processes
  • 🌐 Internationalization: Add multi-language support

📜 License

This project is open source under the Apache 2.0 License.

🙏 Acknowledgments

Thanks to all developers and users who contributed to the project!

Core Contributors:

  • yzfly - Project creator and main maintainer

Special Thanks:

  • Anthropic for Claude Code technical support
  • All community members who provided feedback and suggestions

🔗 Related Links

💬 Community Support

  • WeChat Group: Add WeChat (1796060717) to join LangGPT exchange group
  • WeChat Official Account: 云中江树 (Cloud Tree)
  • GitHub: @yzfly

If this project helps you, please give it a ⭐️

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Made with ❤️ by yzfly

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