How is the checkpoint data stored?

Checkpoints are stored in the .claude/checkpoints/ directory, which includes metadata.json, feature lists, and git reference data.

What does AC Checkpoint Manager do?

It creates snapshots of your project state, including files and git references, allowing you to roll back changes if something goes wrong during development.

When are checkpoints created automatically?

Auto-checkpoints are triggered before starting new features, after completing features, before risky operations, and during context compaction.

Does this tool replace Git?

No, it works alongside Git by tracking git-refs, providing a more granular and automated way to manage states specifically during AI-driven development tasks.

Can I create manual checkpoints?

Yes, the skill supports manual checkpoint creation whenever you want to save a specific milestone or stable state.

AC Checkpoint Manager

Name: AC Checkpoint Manager
Author: adaptationio

byadaptationio

Developer Tools

Manages state snapshots and rollbacks to ensure safe, autonomous development cycles.

About

AC Checkpoint Manager provides a robust safety net for autonomous coding agents by creating automated and manual restore points throughout the development lifecycle. It captures file states, git references, and execution metadata, allowing developers or autonomous systems to instantly revert to a 'known-good' state if a task fails or produces undesirable results. This tool is essential for high-risk refactoring, experimental feature development, and maintaining project consistency during long-running autonomous sessions.

Key Features

Comprehensive metadata tracking including git-refs and execution state
Seamless restoration of previous project states to recover from errors
0 GitHub stars
Manual snapshot creation for specific development milestones
Automatic checkpointing before risky operations and feature starts
Integration with state tracking and task execution workflows

Use Cases

Reverting code to a stable state after an experimental refactor fails
Creating recovery points during long-running autonomous coding sessions
Verifying system integrity by restoring to specific feature-complete milestones

About

Key Features

Comprehensive metadata tracking including git-refs and execution state
Seamless restoration of previous project states to recover from errors
0 GitHub stars
Manual snapshot creation for specific development milestones
Automatic checkpointing before risky operations and feature starts
Integration with state tracking and task execution workflows

Use Cases

Reverting code to a stable state after an experimental refactor fails
Creating recovery points during long-running autonomous coding sessions
Verifying system integrity by restoring to specific feature-complete milestones