"""Create recovery_planner
Generated by Phi-Octopus Eden
2025-11-05 22:32:01.974001
"""

```python
from typing import List


class RecoveryPlanner:
    """
    A class to manage limited error recovery in a system.
    
    Attributes:
        max_retries (int): Maximum number of retries before giving up.
        retry_delay (float): Time delay between retries, in seconds.
    """

    def __init__(self, max_retries: int = 3, retry_delay: float = 2.0):
        self.max_retries = max_retries
        self.retry_delay = retry_delay

    def plan_recovery(self, task_function) -> bool:
        """
        Plan recovery actions for a given task.

        Args:
            task_function (callable): The function representing the task to be executed and recovered from errors.

        Returns:
            bool: True if the task was successfully completed with recovery, False otherwise.
        """
        retries = 0
        while retries < self.max_retries:
            try:
                result = task_function()
                if result is not None and isinstance(result, bool):
                    return result
            except Exception as e:
                print(f"Task failed: {e}")
                retries += 1
                import time
                time.sleep(self.retry_delay)
        print("Maximum retries reached. Giving up.")
        return False


def example_task() -> bool:
    """
    A sample task that may fail and needs recovery.
    
    Returns:
        bool: Task success status.
    """
    # Simulate a failure by throwing an exception or returning False
    import random
    if random.choice([True, False]):
        print("Task failed due to simulated error.")
        return False
    else:
        print("Task executed successfully.")
        return True


if __name__ == "__main__":
    planner = RecoveryPlanner()
    success = planner.plan_recovery(example_task)
    print(f"Final Task Success Status: {success}")
```

This Python script defines a `RecoveryPlanner` class to handle limited error recovery for tasks. The `plan_recovery` method attempts to execute the provided task function up to a specified number of times before giving up, with a delay between retries. The example usage demonstrates how to use this class with a sample task function that simulates failure conditions.