Checkpoints

Checkpoints

When working with AI coding assistants, it's easy to lose control as they make rapid changes to your codebase. That's why we built Checkpoints - your safety net for experimenting confidently.

Checkpoints automatically save snapshots of your workspace after each step in a task. This powerful feature lets you:

• Track and review changes made during a task

• Roll back to any previous point if needed

• Experiment confidently with auto-approve mode

• Maintain full control over your workspace

⚙️ How Checkpoints Work

Cline creates a checkpoint after each tool use (file edits, commands, etc.). These checkpoints:

• Work alongside your Git workflow without interference

• Maintain context between restores

• Use a shadow Git repository to track changes

For example, if you're working on a feature and Cline makes multiple file changes, each change creates a checkpoint. This means you can review each modification and, if needed, roll back to any point without affecting your main Git repository.

Viewing Changes & Restoring to Checkpoint

After each tool use, you can:

1. Click the "Compare" button to see modified files

2. Click the "Restore" button to open restore options

Rolling Back

To restore to a previous point:

1. Click the "Restore" button next to any step

2. Choose from three options:

   • Restore Task and Workspace: Reset both codebase and task to that point

   • Restore Task Only: Keep codebase changes but revert task context

   • Restore Workspace Only: Reset codebase while preserving task context

Example: If Cline makes changes you don't like while styling a component, you can use "Restore Workspace Only" to revert the code changes while keeping the conversation context, allowing you to try a different approach.

💡 Use Cases

Checkpoints let you be more experimental with Cline. While human coding is often methodical and iterative, AI can make substantial changes quickly. Checkpoints help you track these changes and revert if needed.

1. Using Auto-Approve Mode

• Provides safety net for rapid iterations

• Makes it easy to undo unexpected results

2. Testing Different Approaches

• Try multiple solutions confidently

• Compare different implementations

• Quickly revert to working states

• Ideal for exploring different design patterns or architectural approaches