### Body

There are some use cases where users want to trigger new DAG run as soon as one finished. This is a request I've seen several times with some variations (for example like this [Stackoverflow question](https://stackoverflow.com/q/75623153/14624409)) but the basic request is the same.

The workaround users do to get such functionality is place `TriggerDagRunOperator` as last task of their DAG invoking the same DAG:

```
from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule=None,
) as dag:
    task = EmptyOperator(task_id="first")
    trigger = TriggerDagRunOperator(
        task_id="trigger",
        trigger_dag_id="example",
    )

    task >> trigger

```

As you can see this works nicely:
![Screenshot 2023-03-03 at 14 20 51](https://user-images.githubusercontent.com/45845474/222718862-dfde8a41-24b6-4991-b318-b7f9784514f6.png)

My suggestion is to add first class support for this use case, so the above example will be changed to:

```

from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule="@continues",
) as dag:
    task = EmptyOperator(task_id="first")
```

I guess it won't exactly be `"@continues"` but more likely new [ScheduleArg](https://github.com/apache/airflow/blob/8b8552f5c4111fe0732067d7af06aa5285498a79/airflow/models/dag.py#L127) type but I show it like that just for simplification of the idea.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
(DEFAULT_DATE, None),
            [
                (DEFAULT_DATE + timedelta(days=1), DEFAULT_DATE + timedelta(days=2)),
                (DEFAULT_DATE + timedelta(days=3), DEFAULT_DATE + timedelta(days=4)),
            ],
            TimeRestriction(DEFAULT_DATE, DEFAULT_DATE + timedelta(days=4), True),
        ],
        [
            (DEFAULT_DATE, None),
            [(DEFAULT_DATE, DEFAULT_DATE + timedelta(days=1)), (DEFAULT_DATE, None)],
            TimeRestriction(DEFAULT_DATE, None, True),
        ],
    ],
)
def test__time_restriction(dag_maker, dag_date, tasks_date, restrict):
    with dag_maker("test__time_restriction", start_date=dag_date[0], end_date=dag_date[1]) as dag:
        EmptyOperator(task_id="do1", start_date=tasks_date[0][0], end_date=tasks_date[0][1])
        EmptyOperator(task_id="do2", start_date=tasks_date[1][0], end_date=tasks_date[1][1])
    assert dag._time_restriction == restrict
@pytest.mark.parametrize(
    "tags, should_pass",
    [
        pytest.param([], True, id="empty tags"),
        pytest.param(["a normal tag"], True, id="one tag"),
        pytest.param(["a normal tag", "another normal tag"], True, id="two tags"),
        pytest.param(["a" * 100], True, id="a tag that's of just length 100"),
        pytest.param(["a normal tag", "a" * 101], False, id="two tags and one of them is of length > 100"),
    ],
)
def test__tags_length(tags: list[str], should_pass: bool):