checkpoint-management
Git-backed state management for safe rollback. Create and restore checkpoints with tagged commits and metadata tracking.
npx skills add a5c-ai/babysitter --skill checkpoint-management --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
- Stage all current changes - Create commit with [CHECKPOINT] prefix - Tag with claudekit-checkpoint-{timestamp} - Record metadata: files changed, insertions, deletions ### Restore Checkpoint - List available checkpoints by tag - Preview changes that would be reverted - Restore to selected checkpoint via git reset - Verify restored state matches checkpoint ## Session Isolation Checkpoints are session-scoped. Tags created during a session can be cleaned up without affecting other work. ## When to Use - Before risky refactoring operations - After passing quality checks (safety checkpoints) - At the start and end of ClaudeKit sessions - Before spec execution phases ## Processes Used By - `claudekit-orchestrator` (session start/end checkpoints) - `claudekit-safety-pipeline` (safety checkpoints after quality checks)
- Restore Checkpoint
- Session Isolation
- When to Use
- Processes Used By
What does the checkpoint-management skill do?
Git-backed state management for safe rollback. Create and restore checkpoints with tagged commits and metadata tracking.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill checkpoint-management --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.