> ## Documentation Index
> Fetch the complete documentation index at: https://docs.adenhq.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Install Hive and reach your first success — a running, goal-driven agent — in under 10 minutes

By the end of this guide, you'll have Hive installed and your first agent running. That's your **First Success** — and everything from here should be smooth.

## Prerequisites

<CardGroup cols={2}>
  <Card title="Python 3.11+" icon="python">
    Python 3.11, 3.12, or 3.13. Check with `python --version`.
  </Card>

  <Card title="LLM API Key" icon="key">
    An API key for Anthropic, OpenAI, Gemini, or another LiteLLM-supported provider.
  </Card>
</CardGroup>

<Info>
  **Windows users:** Use WSL (Windows Subsystem for Linux) or Git Bash. Some automation scripts may not run correctly in standard Command Prompt or PowerShell.
</Info>

## Step 1: Clone and Install

```bash theme={null}
git clone https://github.com/adenhq/hive.git
cd hive
./quickstart.sh
```

The setup wizard handles everything:

* Checks Python and installs `uv` if needed
* Installs workspace packages (`framework` and `aden_tools`)
* Installs Playwright browser dependencies when available
* Verifies imports and local environment health
* Guides LLM provider configuration

<Accordion title="Manual setup (if the wizard fails)">
  ```bash theme={null}
  # Install dependencies
  uv sync

  # Verify everything works
  uv run python -c "import framework; print('framework OK')"
  uv run python -c "import aden_tools; print('aden_tools OK')"
  uv run python -c "import litellm; print('litellm OK')"
  ```
</Accordion>

## Step 2: Set Up Your LLM Provider

Export at least one provider API key:

```bash theme={null}
export ANTHROPIC_API_KEY="sk-ant-..."
```

<Tip>
  The quickstart script can detect existing keys in your environment and generate a default Hive provider configuration automatically.
</Tip>

## Step 3: Build Your First Agent

Use your coding agent to create an agent through a guided conversation:

```bash theme={null}
claude> /hive
```

This walks you through defining your goal, generating the agent graph, and setting up the required nodes and edges. No manual wiring needed.

## Step 4: Test It

Run your agent interactively to see it work:

```bash theme={null}
# Interactive dashboard
hive tui

# Or run directly with input
hive run exports/your_agent_name --input '{"task": "Your input here"}'
```

<Check>
  **First Success!** If your agent ran and produced output, you've reached the milestone. Everything from here — debugging, deployment, iteration — builds on this foundation.
</Check>

## What Just Happened

When you built your agent, Hive:

1. **Parsed your goal** into structured success criteria and constraints
2. **Generated a node graph** with the right nodes, edges, and connection code
3. **Wrapped each node** with the SDK — giving it memory, LLM access, tools, and observability
4. **Ran the graph** against your input, evaluating outcomes at each step

## Alternative: Start From a Template

If you'd rather start from something that already works and customize it:

```bash theme={null}
# Browse available agents
hive tui

# Or copy an existing template and make it yours
```

See [Build From Existing Agent](/building/build-with-existing-agent) for the full workflow.

## Next Steps

<CardGroup cols={2}>
  <Card title="Build Your Own Agent" icon="hammer" href="/building/first-agent">
    Detailed guide to creating custom goal-driven agents.
  </Card>

  <Card title="Use Case Templates" icon="grid-2" href="/getting-started/use-cases">
    Browse ready-made agents you can deploy or customize.
  </Card>

  <Card title="Core Concepts" icon="lightbulb" href="/building-agent/concepts/overview">
    Understand goals, graphs, and the runtime model.
  </Card>

  <Card title="Testing" icon="vial" href="/building/testing">
    Add goal-based tests before deploying to production.
  </Card>
</CardGroup>