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

# ARC-AGI-3 Quickstart

> ARC-AGI-3 is an Interactive Reasoning Benchmark designed to measure an AI Agent's ability to generalize in novel, unseen environments.

<div style={{ display: 'flex', alignItems: 'flex-start', gap: '1rem' }}>
  <div style={{ flex: 1 }}>
    <p>
      Traditionally, to measure AI, static benchmarks have been the yardstick.
      These work well for evaluating LLMs and AI reasoning systems. However, to evaluate frontier AI agent systems, we
      need new tools that measure:
    </p>

    <ul>
      <li>Exploration</li>
      <li>Percept → Plan → Action</li>
      <li>Memory</li>
      <li>Goal Acquisition</li>
      <li>Alignment</li>
    </ul>

    <p>
      By building agents that can play ARC-AGI-3, you're directly contributing
      to the frontier of AI research. <br /><br /> Learn more about{' '}
      <a href="https://arcprize.org/arc-agi/3">ARC-AGI-3</a>.
    </p>
  </div>

  <div style={{ flex: 1, textAlign: 'center' }}>
    <img src="https://mintcdn.com/arcprizefoundation/sx3SsV7kmM_q56IF/images/Ls20Human.gif?s=61025c7aeb245af080aba9e735a6f1cf" alt="Human playing LS20" width="512" height="512" data-path="images/Ls20Human.gif" />

    <p>
      Can you build an agent to beat{' '}
      <a href="https://arcprize.org/tasks/ls20">this game</a>?
    </p>
  </div>
</div>

## Play your first ARC-AGI-3 environment

### 1. Install the [ARC-AGI Toolkit](https://github.com/arcprize/arc-agi)

```bash theme={null}
uv init
uv add arc-agi
# or
pip install arc-agi
```

### 2. Set your `ARC_API_KEY`

Optionally set your `ARC_API_KEY`. If no key is provided, an anonymous key will be used. However, registering for an API key will give you access to public games at release. [Get an ARC\_API\_KEY](/api-keys)

```bash theme={null}
export ARC_API_KEY="your-api-key-here"
# or
echo 'ARC_API_KEY=your-api-key-here' > .env
```

### 3. Play your first game

Create a file called `my-play.py`:

```python theme={null}
import arc_agi
from arcengine import GameAction

arc = arc_agi.Arcade()
env = arc.make("ls20", render_mode="terminal")

# Take a few actions
for _ in range(10):
    env.step(GameAction.ACTION1)

print(arc.get_scorecard())
```

Run it:

```bash theme={null}
python play.py
```

You should see the game render in your terminal and a scorecard with your results.

🎉 Congratulations! You just played your first ARC-AGI-3 environment programatically.

Do you feel the AGI yet?

## Next Steps

After running your first environment:

1. **Make it fast** - Use `env = arc.make("ls20")` without `render_mode` to hit +2K FPS
2. **Try a different game** - Run `env = arc.make("ft09", render_mode="terminal")` to play a another game. See a list of games available at [arcprize.org/tasks](https://arcprize.org/tasks) or via the [ARC-AGI Toolkit](/toolkit/list-games)
3. **Use an agent** - Explore [agent templates](/llm_agents) or [create your own agent](/agents-quickstart).
4. **Explore the ARC-AGI Toolkit** - [The ARC-AGI Toolkit](./toolkit/overview) allows quick and easy integration with ARC-AGI Environments.