Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
A Python execution wrapper that automatically categorizes errors and applies recovery strategies, including retries with exponential backoff, dependency installation, and resource creation. Supports checkpoint/resume for long-running jobs and overnight batch queuing. Logs all execution history to MongoDB.
Eliminates boilerplate retry and error-handling code by wrapping any function with categorized recovery logic out of the box.
When to use it
- Queue overnight batch deployments to run while sleeping
- Retry flaky API calls without writing custom retry logic
- Resume a long task from a checkpoint after a failure
- Auto-install missing Python packages mid-execution
- Review morning reports on overnight task outcomes
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: deploy my portfolio project overnight and report results in the morning
- 1Import Overnight from autonomous_executor.overnight
- 2Queue the deploy task with Overnight.deploy('my-portfolio', 'portfolio')
- 3Call Overnight.start() to begin scheduled execution
- 4Executor retries on network or rate-limit failures using exponential backoff
- 5Checkpoints progress so execution can resume if interrupted
Morning report showing task completion status, retry attempts, duration, and any errors encountered
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.