> ## 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.

# Submit Action

> How to submit actions and include reasoning logs using the ARC-AGI Toolkit

## Overview

Once you know which actions are available, you can submit them to the environment using the `step()` method on the `EnvironmentWrapper`. This method also supports including reasoning logs with each action.

## Submitting a simple action

Use the `step()` method to submit an action:

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

# Submit a simple action
obs = env.step(GameAction.ACTION1)

# Check the result
if obs:
    print(f"Game state: {obs.state}")
```

## Submitting a complex action

Complex actions require additional data, such as x,y coordinates:

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

# Submit a complex action with coordinates
obs = env.step(
    GameAction.ACTION6,
    data={"x": 32, "y": 32}
)
```

## Including reasoning logs

The `step()` method accepts an optional `reasoning` parameter that allows you to include reasoning metadata with each action. This is useful for tracking your agent's thought process in recordings.

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

# Submit an action with reasoning logs
obs = env.step(
    GameAction.ACTION1,
    reasoning={"thought": "Selecting this action because the pattern suggests a left shift"}
)

# Complex action with both data and reasoning
obs = env.step(
    GameAction.ACTION6,
    data={"x": 32, "y": 32},
    reasoning={
        "thought": "clicking center of screen",
        "confidence": 0.85,
        "alternatives_considered": ["top-left", "bottom-right"]
    }
)
```

The reasoning dictionary can contain any key-value pairs you want to track. Common fields include:

* `thought`: A description of why the action was chosen
* `confidence`: A confidence score for the action
* `alternatives_considered`: Other actions that were considered
* `reasoning_tokens`: Token count from reasoning models

## Checking the result

After submitting an action, check the returned `FrameDataRaw` object:

```python theme={null}
from arcengine import GameState

obs = env.step(GameAction.ACTION1)

if obs:
    if obs.state == GameState.WIN:
        print("Game won!")
    elif obs.state == GameState.GAME_OVER:
        print("Game over, resetting...")
        env.reset()
```

## Next steps

* [List available actions](./list-actions)
* [Build a game-playing script](./minimal)