### 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)

dag_ids: list[str], *, session: Session
) -> dict[str, dict[str, int | str]]:
    """
    Get next run info for a list of dag_ids.
    Given a list of dag_ids, get string representing how close any that are dataset triggered are
    their next run, e.g. "1 of 2 datasets updated".
    """
    from airflow.models.dataset import DagScheduleDatasetReference, DatasetDagRunQueue as DDRQ, DatasetModel
    return {
        x.dag_id: {
            "uri": x.uri,
            "ready": x.ready,
            "total": x.total,
        }
        for x in session.execute(
            select(
                DagScheduleDatasetReference.dag_id,
                
                
                case((func.count() == 1, func.max(DatasetModel.uri)), else_="").label("uri"),
                func.count().label("total"),
                func.sum(case((DDRQ.target_dag_id.is_not(None), 1), else_=0)).label("ready"),
            )
            .join(
                DDRQ,
                and_(
                    DDRQ.dataset_id == DagScheduleDatasetReference.dataset_id,
                    DDRQ.target_dag_id == DagScheduleDatasetReference.dag_id,
                ),