---
description: Context management for maintaining codebase awareness and preventing context drift
globs: 
alwaysApply: false
---

# Rule: Context Management

## Goal
Maintain comprehensive project context to prevent context drift and ensure AI-generated code integrates seamlessly with existing codebase patterns and architecture.

## Context Documentation Requirements

### PRD.md file documentation
1. **Project Overview**
   - Business objectives and goals
   - Target users and use cases
   - Key success metrics

### CONTEXT.md File Structure
Every project must maintain a `CONTEXT.md` file in the root directory with:

1. **Architecture Overview**
   - High-level system architecture
   - Key design patterns used
   - Database schema overview
   - API structure and conventions

2. **Technology Stack**
   - Programming languages and versions
   - Frameworks and libraries
   - Database systems
   - Development and deployment tools

3. **Coding Conventions**
   - Naming conventions
   - File organization patterns
   - Code structure preferences
   - Import/export patterns

4. **Current Implementation Status**
   - Completed features
   - Work in progress
   - Known technical debt
   - Planned improvements

## Context Maintenance Protocol

### Before Every Coding Session
1. **Review CONTEXT.md and PRD.md** to understand current project state
2. **Scan recent changes** in git history to understand latest patterns
3. **Identify existing patterns** for similar functionality before implementing new features
4. **Ask for clarification** if existing patterns are unclear or conflicting

### During Development
1. **Reference existing code** when explaining implementation approaches
2. **Maintain consistency** with established patterns and conventions
3. **Update CONTEXT.md** when making architectural decisions
4. **Document deviations** from established patterns with reasoning

### Context Preservation Strategies
- **Incremental development**: Build on existing patterns rather than creating new ones
- **Pattern consistency**: Use established data structures and function signatures
- **Integration awareness**: Consider how new code affects existing functionality
- **Dependency management**: Understand existing dependencies before adding new ones

## Context Prompting Best Practices

### Effective Context Sharing
- Include relevant sections of CONTEXT.md in prompts for complex tasks
- Reference specific existing files when asking for similar functionality
- Provide examples of existing patterns when requesting new implementations
- Share recent git commit messages to understand latest changes

### Context Window Optimization
- Prioritize most relevant context for current task
- Use @filename references to include specific files
- Break large contexts into focused, task-specific chunks
- Update context references as project evolves

## Red Flags - Context Loss Indicators
- AI suggests patterns that conflict with existing code
- New implementations ignore established conventions
- Proposed solutions don't integrate with existing architecture
- Code suggestions require significant refactoring of existing functionality

## Recovery Protocol
When context loss is detected:
1. **Stop development** and review CONTEXT.md
2. **Analyze existing codebase** for established patterns
3. **Update context documentation** with missing information
4. **Restart task** with proper context provided
5. **Test integration** with existing code before proceeding