Every interaction with Cline happens within a task. Tasks are self-contained work sessions that capture your entire conversation, code changes, command executions, and decisions.
What are Tasks?
A task begins when you submit a prompt to Cline. Your prompt defines the goal, and Cline works toward it through conversation, code changes, and tool use. The quality of your initial prompt directly affects how well Cline performs - clear, specific prompts lead to better results.
Each task:
- Starts with your prompt and builds context through the conversation
- Has a unique identifier and dedicated storage directory
- Contains the full conversation history
- Tracks token usage, API costs, and execution time
- Can be interrupted and resumed across sessions
- Creates checkpoints for file changes through Git-based snapshots
Want to get better results from Cline? Learn how to write effective prompts in our Prompt Module. Scoping Your Tasks
Each task carries its own context: the conversation history, decisions made, and understanding built up over the session. How you scope your tasks directly affects how well Cline can help you.
Think of it this way: one task = one goal. “Implement user authentication” is one task. “Fix an unrelated CSS bug” is a separate task, even if you notice it while working on auth.
A focused task produces better results. When a task tries to cover too many unrelated goals, the context becomes cluttered and responses become less relevant.
If you’re unsure, err on the side of starting fresh. Use task favorites to bookmark successful sessions you might want to reference later.
Context Window
Every AI model has a context window - a limit on how much information it can process at once. Think of it as Cline’s working memory for the current task.
As you work, the context window fills up with:
- Your prompts and Cline’s responses
- File contents Cline reads or edits
- Command outputs and tool results
- System instructions that guide Cline’s behavior
When the context window approaches its limit, Cline automatically compresses older parts of the conversation to make room. This means very long tasks may lose some earlier details, though Cline preserves the most important context.
This is why task scoping matters: a focused task keeps relevant information in the context window. A sprawling task fills the window with noise, pushing out useful context.
For long-running tasks, enable Auto-Compact to intelligently manage context as you work. New Task vs. Continue
Knowing when to start fresh versus continue can feel unclear at first. As you work with Cline more, you’ll develop an intuition for it. Use this table as a starting point:
| Scenario | Action | Why |
|---|
| Switching to a different feature | New task | Clean context, focused responses |
| Building on work Cline just completed | Continue | Shared understanding preserved |
| Cline keeps going off-track | New task | Fighting context wastes time |
| Iterating on the same files | Continue | Conversation history helps |
| Explaining what to ignore | New task | Cluttered context hurts quality |
| Refining Cline’s last output | Continue | Momentum and decisions preserved |
/newtask command. Your file changes are preserved through checkpoints, and you can reference previous tasks from history anytime.
Understanding Task Costs
Every cloud-based AI model charges for usage based on tokens, the units of text the model processes. Cline tracks these costs automatically and displays them in the task header so you can monitor spending as you work.
How Costs Are Calculated
When you interact with Cline, the model processes:
- Input tokens: Your prompts, file contents, conversation history, and system instructions
- Output tokens: The model’s responses, code suggestions, and tool calls
Cloud providers charge per million tokens, with output tokens typically costing more than input. Some providers also support prompt caching, which reduces costs when the same context (like your cline rules or large files) appears in multiple requests. Cline automatically tracks cache savings when available.
The estimated cost shown in the task header updates after each API request. This estimate uses the pricing information from your selected provider and may vary slightly from your final bill depending on how your provider rounds or bills usage.
When You Pay
You pay for AI usage when using cloud providers like Anthropic, OpenAI, OpenRouter, or Google. Costs vary significantly:
| Provider Type | Billing Model |
|---|
| Cline Provider | Pay-per-use with credits you purchase |
| Direct API keys | Billed by your provider (Anthropic, OpenAI, etc.) |
| OpenRouter/Requesty | Aggregated billing across multiple models |
| Local models | Free (you provide the hardware) |
Free Options
Not ready to pay? Cline offers several free paths:
- Free models: Search “free” in the model selector when using the Cline provider. These models display a FREE tag and work well for learning and experimentation.
- Free tiers: Some providers offer limited free usage when you use your own API key.
- Local models: Run models on your own hardware with zero per-request costs.
Self-Hosted Models
Running models locally means no API costs, ever. Your only expense is the hardware to run them.
To run local models effectively, you need:
- 32GB RAM minimum for entry-level models (4-bit quantization)
- 64GB RAM for better quality (8-bit quantization)
- 128GB+ RAM for cloud-competitive performance
The trade-off is speed. Local models run at 5-20 tokens per second on typical hardware, compared to hundreds of tokens per second from cloud APIs. They also require more setup and configuration.
If you have the hardware, local models offer unlimited experimentation with complete privacy. See Running Models Locally to get started. Task History
Every task you work on is saved automatically to your local machine. You can revisit past conversations, resume interrupted work, or reference successful approaches from earlier sessions.
Finding Your History
Click the History button in the Cline sidebar (clock icon at the top-right) to open the history view. You’ll see all your past tasks with their initial prompt, timestamp, and token usage. Each task card expands to show a preview of the conversation.
Searching Tasks
Use the search bar at the top of the history view to find specific tasks. The fuzzy search looks across everything: your prompts, Cline’s responses, code snippets, and file names.
Sort results by:
- Newest/Oldest for chronological browsing
- Most Expensive/Most Tokens to find resource-heavy tasks
- Most Relevant when searching for specific content
- Favorites to show only starred tasks
Use favorites strategically. Star tasks that represent successful patterns, good prompts, or complex work you might want to reference later. Favorited tasks are protected from deletion.
Resuming Tasks
Cline can resume interrupted tasks with full context:
- Open the task from history
- Cline loads the complete conversation
- File states are checked against checkpoints
- The task continues with awareness of the interruption
- Provide additional context if needed
This works across sessions. Even if you close the editor and return days later, Cline can pick up where you left off. 
