Checkpoint
This "Checkpoint" skill verifies if a prompt adheres to specific constraints, ensuring consistent and reliable outputs for your AI interactions.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add checkpoint npx -- -y @trustedskills/checkpoint
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"checkpoint": {
"command": "npx",
"args": [
"-y",
"@trustedskills/checkpoint"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The checkpoint skill allows an AI agent to save its current state and later restore that state. This is useful for long-running tasks or when an agent needs to resume work after interruption. It enables the agent to remember previous steps, decisions, or data, ensuring continuity in complex workflows.
When to use it
- Long Task Resumption: If a task might be interrupted (e.g., due to network issues), checkpointing allows resuming from where it left off.
- Experimentation & Rollback: An agent can create checkpoints before trying risky actions, allowing for easy rollback if things go wrong.
- Complex Workflows: For multi-stage processes, checkpoints ensure that the agent doesn't lose progress in any stage.
- Debugging: Checkpoints provide snapshots of the agent’s state which are useful when troubleshooting unexpected behavior.
Key capabilities
- State saving and restoration
- Workflow continuity
- Rollback functionality
- Snapshot creation
Example prompts
- "Create a checkpoint before I start generating this report."
- "Restore my last checkpoint."
- "Save the current state as 'draft_v1'."
- “Go back to the ‘planning’ checkpoint.”
Tips & gotchas
The effectiveness of checkpoint depends on how well the agent's internal state is captured. Ensure that any external dependencies or resources are also saved or restored alongside the agent's core state for complete recovery.
Tags
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