A self-healing execution engine that provides AI agents with full autonomy to recover from errors and process batch tasks overnight.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install autonomous-executor
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install autonomous-executor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Autonomous Executor?
The Autonomous Executor is a sophisticated self-healing engine designed to empower Openclaw Skills with complete operational autonomy. It intelligently monitors task execution, identifying failures across categories such as network, authentication, and dependencies. By applying targeted recovery strategies like exponential backoff and automatic resource creation, it ensures that your AI agents remain productive even in unstable environments.
This skill is particularly valuable for developers building long-running or mission-critical automation pipelines. Whether you are running a single complex function or orchestrating an entire batch of overnight tasks, the Autonomous Executor provides the resilience needed to move from fragile scripts to robust, production-grade agentic workflows using Openclaw Skills.
Autonomous Executor Use Cases
- Automating project deployments that require multi-step verification and error handling.
- Executing deep web research tasks that may encounter rate limits or connection timeouts.
- Scheduling and running batch processing jobs overnight without manual supervision.
- Building resilient API integrations that need to self-correct during intermittent outages.
How Autonomous Executor Works
- The user or agent triggers a task via the AutoExec or Overnight API components within the ecosystem of Openclaw Skills.
- The executor analyzes the environment and checks for the required capabilities among available tools.
- During execution, the system monitors for exceptions and classifies them into specific categories like Network, Auth, or Dependency.
- If an error occurs, the engine applies the corresponding recovery strategy, such as waiting for a retry-after header or auto-installing a missing library.
- The execution progress is saved to checkpoints in MongoDB, allowing for resumes if a terminal failure occurs.
- A final report is generated, logging every attempt, recovery action, and the ultimate outcome for review.
Autonomous Executor Setup
Install the package using pip or include it in your project environment. Ensure a MongoDB instance is accessible for logging and checkpoints.
pip install autonomous-executor
Configure your environment variables to point to your database:
export MONGODB_URI="mongodb://localhost:27017"
Autonomous Executor Data Schema & Taxonomy
The skill utilizes MongoDB to maintain persistence and provide observability into autonomous operations managed by Openclaw Skills.
| Collection | Description |
|---|---|
| task_records | Detailed logs of every execution, including parameters and final status. |
| task_checkpoints | Serialization of task states to enable the checkpoint and resume feature. |
| execution_logs | Real-time stream of logs generated during the lifecycle of a task. |
Autonomous Executor Advanced Features
- Overnight Batch Execution: Queue multiple long-running tasks to run autonomously while you are offline.
- Function Decorators: Easily wrap any Python function with @autonomous to inject self-healing capabilities.
- Capability Awareness: Automatically detects and utilizes tools from other Openclaw Skills in the ecosystem.
- Exponential Backoff: Smart retry timing that prevents overloading services during outages.
SKILL.md
Loading
Related Openclaw Skills
Alert System
A robust monitoring agent that tracks price fluctuations and web events to send real-time Telegram notifications.
LiteLLM
LiteLLM provides a unified API interface to call over 100 LLM providers seamlessly within your AI agent workflows.
Find Skills
A command-line utility to discover, install, and manage new capabilities for your AI agent through the Openclaw Skills marketplace.
AutoGLM ASR MCP
A high-performance Model Context Protocol server for concurrent audio-to-text transcription powered by GLM-ASR-2512.
Mao Yan Cinema CLI Skill
A Python-based CLI tool for querying Mao Yan cinema schedules, movie availability, and theater metadata in real-time.
Code QC: Automated Codebase Quality Audit
A structured 8-phase quality control tool that automates code audits, static analysis, and smoke testing for multiple programming languages.
Featured*
