Understanding Context Management
Context is key to getting the most out of Cline
Last updated
Context is key to getting the most out of Cline
Last updated
💡 Quick Reference
Context = The information Cline knows about your project
Context Window = How much information Cline can hold at once
Use context files to maintain project knowledge
Reset when the context window gets full
Think of working with Cline like collaborating with a thorough, proactive teammate:
Cline actively builds context in two ways:
Automatic Context Gathering (i.e. Cline-driven)
Proactively reads related files
Explores project structure
Analyzes patterns and relationships
Maps dependencies and imports
Asks clarifying questions
User-Guided Context
Share specific files
Provide documentation
Answer Cline's questions
Guide focus areas
Share design thoughts and requirements
💡 Key Point: Cline isn't passive - it actively seeks to understand your project. You can either let it explore or guide its focus, especially in Plan mode.
Think of context like a whiteboard you and Cline share:
Context is all the information available:
What Cline has discovered
What you've shared
Your conversation history
Project requirements
Previous decisions
Context Window is the size of the whiteboard itself:
Measured in tokens (1 token ≈ 3/4 of an English word)
Each model has a fixed size:
Claude 3.5 Sonnet: 200,000 tokens
DeepSeek: 64,000 tokens
When the whiteboard is full, you need to erase (clear context) to write more
⚠️ Important: Having a large context window (like Claude's 200k tokens) doesn't mean you should fill it completely. Just like a cluttered whiteboard, too much information can make it harder to focus on what's important.
Cline provides a visual way to monitor your context window usage through a progress bar:
↑ shows input tokens (what you've sent to the LLM)
↓ shows output tokens (what the LLM has generated)
The progress bar visualizes how much of your context window you've used
The total shows your model's maximum capacity (e.g., 200k for Claude 3.5-Sonnet)
During long coding sessions
When working with multiple files
Before starting complex tasks
When Cline seems to lose context
💡 Tip: Consider starting a fresh session when usage reaches 70-80% to maintain optimal performance.
Context files help maintain understanding across sessions. They serve as documentation specifically designed to help AI assistants understand your project.
Evergreen Project Context (i.e. Memory Bank)
Living documentation that evolves with your project
Updated as architecture and patterns emerge
Example: The Memory Bank pattern maintains files like techContext.md
and systemPatterns.md
Useful for long-running projects and teams
Task-Specific Context (i.e. Structured Approach)
Created for specific implementation tasks
Document requirements, constraints, and decisions
Example:
Structure and Format
Use clear, consistent organization
Include relevant examples
Link related concepts
Keep information focused
Maintenance
Update after significant changes
Version control your context files
Remove outdated information
Document key decisions
Starting New Projects
Let Cline explore the codebase
Answer its questions about structure and patterns
Consider setting up basic context files
Document key design decisions
Ongoing Development
Update context files with significant changes
Share relevant documentation
Use Plan mode for complex discussions
Start fresh sessions when needed
Team Projects
Share common context files (consider using .clinerules files in project roots)
Document architectural decisions
Maintain consistent patterns
Keep documentation current
Remember: The goal is to help Cline maintain consistent understanding of your project across sessions.