### 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)

max_active_runs = Column(Integer, nullable=True)
    has_task_concurrency_limits = Column(Boolean, nullable=False)
    has_import_errors = Column(Boolean(), default=False, server_default="0")
    
    next_dagrun = Column(UtcDateTime)
    
    next_dagrun_data_interval_start = Column(UtcDateTime)
    next_dagrun_data_interval_end = Column(UtcDateTime)
    
    next_dagrun_create_after = Column(UtcDateTime)
    __table_args__ = (
        Index("idx_root_dag_id", root_dag_id, unique=False),
        Index("idx_next_dagrun_create_after", next_dagrun_create_after, unique=False),
    )
    parent_dag = relationship(
        "DagModel", remote_side=[dag_id], primaryjoin=root_dag_id == dag_id, foreign_keys=[root_dag_id]
    )
    schedule_dataset_references = relationship(
        "DagScheduleDatasetReference",
        cascade="all, delete, delete-orphan",
    )
    schedule_datasets = association_proxy("schedule_dataset_references", "dataset")
    task_outlet_dataset_references = relationship(
        "TaskOutletDatasetReference",
        cascade="all, delete, delete-orphan",
    )
    NUM_DAGS_PER_DAGRUN_QUERY = airflow_conf.getint(
        "scheduler", "max_dagruns_to_create_per_loop", fallback=10
    )
    def __init__(self, concurrency=None, **kwargs):