A secure, ephemeral environment for executing and verifying AI-generated code across multiple languages using Docker containers.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install docker-docker-sandbox-agent
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 docker-docker-sandbox-agent 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 Docker Sandbox?
The Docker Sandbox skill is designed to solve the critical security challenge of executing unverified code generated by AI agents. By utilizing Openclaw Skills patterns, this tool enables the provisioning of temporary, isolated container environments where code can be tested for accuracy and stability without exposing the host machine to potential vulnerabilities. It provides a standard protocol for agents to verify Python, JavaScript, and Shell scripts in a controlled setting.
Integrating this skill into your workflow ensures that any code produced by an agent is vetted within a sandbox that includes resource constraints and network isolation. This makes Openclaw Skills significantly safer to deploy in production-like environments where stability and security are paramount.
Docker Sandbox Use Cases
- Safely executing Python or Node.js scripts to verify logic before final output.
- Testing shell scripts and system commands in a clean Alpine Linux environment.
- Benchmarking code performance with strict CPU and memory limits.
- Running untrusted third-party snippets without risking host file system exposure.
How Docker Sandbox Works
- The AI agent generates a code snippet and saves it to a local temporary directory designated for sandboxing.
- A Docker container is launched using a runtime-specific image (e.g., python:slim or node:alpine).
- The sandbox directory is mounted to the container as a volume to provide the code context.
- The code is executed with the --rm flag to ensure the container is automatically destroyed after the process exits.
- Standard output and errors are captured and returned to the agent for verification and debugging.
Docker Sandbox Setup
To use this skill within the Openclaw Skills framework, ensure Docker is installed and running on your host system. No additional binary installation is required beyond the Docker engine.
# Verify Docker installation
docker --version
# Pull common runtime images
docker pull python:3.10-slim
docker pull node:18-alpine
docker pull alpine:latest
Docker Sandbox Data Schema & Taxonomy
The skill organizes execution data through a temporary local directory structure that is mapped to the container environment.
| Directory/File | Description |
|---|---|
.sandbox/ |
The designated host directory for all code verification tasks. |
main.py / main.js |
The primary script file generated by the agent for testing. |
stdout/stderr |
Captured streams returned to the Openclaw Skills interface for analysis. |
Docker Sandbox Advanced Features
- Network Isolation: Use the --network none flag to prevent code from making external requests.
- Resource Throttling: Define hard limits on CPU and memory to prevent runaway processes from consuming host resources.
- Ephemeral Filesystems: All changes made inside the container are discarded immediately after execution.
- Host Isolation: Prevents the agent from accessing sensitive host directories like /etc or ~/.ssh.
SKILL.md
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