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OpenShell/docs/get-started/quickstart.md
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---
title:
page: "Quickstart"
nav: "Quickstart"
description: "Install the OpenShell CLI and create your first sandboxed AI agent in two commands."
keywords: ["nemoclaw install", "quickstart", "sandbox create", "getting started"]
topics: ["generative_ai", "cybersecurity"]
tags: ["ai_agents", "sandboxing", "installation", "quickstart"]
content:
type: get_started
difficulty: technical_beginner
audience: [engineer, data_scientist]
---
<!--
SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
SPDX-License-Identifier: Apache-2.0
-->
# Quickstart
This page gets you from zero to a running, policy-enforced sandbox in two commands.
## Prerequisites
Before you begin, make sure you have:
- Python 3.12 or later
- Docker Desktop running on your machine <!-- TODO: add compatible version -->
## Install the OpenShell CLI
```bash
pip install nemoclaw
```
## Create Your First OpenShell Sandbox
Choose the tab that matches your agent:
::::{tab-set}
:::{tab-item} Claude Code
```console
$ nemoclaw sandbox create -- claude
```
```text
✓ Runtime ready
✓ Discovered Claude credentials (ANTHROPIC_API_KEY)
✓ Created sandbox: keen-fox
✓ Policy loaded (4 protection layers active)
Connecting to keen-fox...
```
The CLI detects your `ANTHROPIC_API_KEY`, creates a provider, builds the sandbox, applies a default policy, and drops you into an interactive session. No additional configuration is required.
:::
:::{tab-item} Community Sandbox
```console
$ nemoclaw sandbox create --from openclaw
```
The `--from` flag pulls a pre-built sandbox definition from the [NemoClaw Community](https://github.com/NVIDIA/NemoClaw-Community) catalog. Each definition bundles a container image, a tailored policy, and optional skills into a single package.
:::
::::
## What Happens Behind the Scenes
When you create a sandbox, OpenShell activates the following protection layers.
| Protection Layer | Description |
|------------------------|-----------------------------------------------------------------------------------------------|
| Filesystem isolation | The agent can only read and write paths that the policy explicitly permits. |
| Network enforcement | Outbound connections are denied by default. The policy allowlists specific hosts, ports, and binaries. |
| Process restrictions | The agent runs as a non-root user inside the container. |
| Inference privacy | LLM API traffic is routed through a privacy-aware proxy. Credentials never leak outside the sandbox. |
A single YAML policy file controls all four layers. You can hot-reload network and inference rules on a running sandbox without restarting it.
:::{note}
For OpenCode or Codex, the default policy does not cover the required endpoints. Follow the [Run OpenCode with NVIDIA Inference](run-opencode.md) tutorial for agent-specific setup.
:::
## Next Steps
You now have a working sandbox. From here, you can:
- Follow the [Tutorials](tutorials.md) for step-by-step walkthroughs with Claude Code, OpenClaw, and OpenCode.
- Learn how sandboxes work in [Sandboxes](../sandboxes/create-and-manage.md).
- Write your own policies in [Safety and Privacy](../safety-and-privacy/index.md).