# List functions
result = await aws_lambda_list_functions(region="us-west-2")

# Invoke a function
result = await aws_lambda_invoke(
    function_name="my-function",
    payload='{"key": "value"}',
    region="us-east-1"
)

result = await aws_ses_send_email(
    to="recipient@example.com",
    subject="Hello from SES",
    body="This is a test email.",
    from_addr="sender@example.com"
)

# List running containers
result = await docker_list_containers()

# List all containers (including stopped)
result = await docker_list_containers(all=True)

# Run a container
result = await docker_run_container(
    image="python:3.13-slim",
    command="python -c 'print(\"hello\")'",
    environment={"MY_VAR": "value"}
)

# Stop a container
result = await docker_stop_container(container_id="abc123")

# Create a workspace
result = await daytona_create_workspace(
    repo_url="https://github.com/user/repo"
)

# List workspaces
result = await daytona_list_workspaces()

# Run a command
result = await daytona_run_command(
    workspace_id="ws-123",
    command="ls -la"
)

# Run Python code
result = await e2b_run_code(
    code="print('Hello from E2B!')",
    language="python",
    timeout=60
)

# Run a shell command
result = await e2b_run_command(
    command="pip install requests && python -c 'import requests; print(requests.__version__)'",
    timeout=120
)

# List DAGs
result = await airflow_list_dags()

# Trigger a DAG
result = await airflow_trigger_dag(
    dag_id="my_etl_pipeline",
    conf={"param1": "value1"}
)

# Check DAG run status
result = await airflow_get_dag_run(
    dag_id="my_etl_pipeline",
    run_id="manual__2025-01-01T00:00:00+00:00"
)

{
  "success": true,
  "data": {
    "...": "tool-specific fields"
  }
}

{
  "success": false,
  "error": "Description of what went wrong"
}