### What do you see as an issue?

The [/dags/{dag_id}/details](https://airflow.apache.org/docs/apache-airflow/stable/stable-rest-api-ref.html#operation/post_set_task_instances_state) endpoint of the REST API does not return all of the keys that are listed in the documentation. If I run `curl -X GET localhost:8080/api/v1/dags/{my_dag}/details`, then compare the results with the results in the documentation, you can see the following missing keys:

```python
>>> for key in docs.keys():
...     if not key in actual.keys():
...             print(key)
...
root_dag_id
last_parsed_time
last_pickled
last_expired
scheduler_lock
timetable_description
has_task_concurrency_limits
has_import_errors
next_dagrun
next_dagrun_data_interval_start
next_dagrun_data_interval_end
next_dagrun_create_after
template_search_path
```

### Solving the problem

Either remove these keys from the documentation or fix the API endpoint

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

with_row_locks,
)
from airflow.utils.state import DagRunState, State, TaskInstanceState
from airflow.utils.trigger_rule import TriggerRule
from airflow.utils.types import NOTSET, ArgNotSet, DagRunType, EdgeInfoType
if TYPE_CHECKING:
    from types import ModuleType
    from pendulum.tz.timezone import Timezone
    from sqlalchemy.orm.query import Query
    from sqlalchemy.orm.session import Session
    from airflow.datasets import Dataset
    from airflow.decorators import TaskDecoratorCollection
    from airflow.models.dagbag import DagBag
    from airflow.models.operator import Operator
    from airflow.models.slamiss import SlaMiss
    from airflow.serialization.pydantic.dag import DagModelPydantic
    from airflow.serialization.pydantic.dag_run import DagRunPydantic
    from airflow.typing_compat import Literal
    from airflow.utils.task_group import TaskGroup
log = logging.getLogger(__name__)
DEFAULT_VIEW_PRESETS = ["grid", "graph", "duration", "gantt", "landing_times"]
ORIENTATION_PRESETS = ["LR", "TB", "RL", "BT"]
TAG_MAX_LEN = 100
DagStateChangeCallback = Callable[[Context], None]
ScheduleInterval = Union[None, str, timedelta, relativedelta]
ScheduleIntervalArg = Union[ArgNotSet, ScheduleInterval]
ScheduleArg = Union[ArgNotSet, ScheduleInterval, Timetable, Collection["Dataset"]]
SLAMissCallback = Callable[["DAG", str, str, List["SlaMiss"], List[TaskInstance]], None]
DEFAULT_SCHEDULE_INTERVAL = timedelta(days=1)
class InconsistentDataInterval(AirflowException):