"""Create recovery_planner
Generated by Phi-Octopus Eden
2025-11-08 15:30:37.852364
"""

```python
from typing import Callable, Dict, List


class RecoveryPlanner:
    """
    A class designed to handle limited error recovery in computational processes.
    It allows defining a sequence of actions to recover from errors,
    and executes them in order until an action successfully resolves the issue or all are exhausted.
    """

    def __init__(self):
        self.actions: List[Callable] = []

    def add_recovery_action(self, action: Callable) -> None:
        """
        Adds a recovery action to the planner.

        :param action: A callable function that attempts to resolve an error.
                       It should take no arguments and return True if successful, False otherwise.
        """
        self.actions.append(action)

    def run_recovery_plan(self) -> bool:
        """
        Executes each of the added recovery actions in sequence until one succeeds or all fail.

        :return: True if at least one action successfully resolved an error, False otherwise.
        """
        for action in self.actions:
            success = action()
            if success:
                return True
        return False


# Example usage

def recover_action1() -> bool:
    """Example recovery action 1."""
    print("Executing recovery action 1")
    # Simulate a successful recovery
    return True


def recover_action2() -> bool:
    """Example recovery action 2."""
    print("Executing recovery action 2")
    # Simulate an unsuccessful recovery
    return False


# Create a RecoveryPlanner instance
recovery_plan = RecoveryPlanner()

# Add actions to the planner
recovery_plan.add_recovery_action(recover_action1)
recovery_plan.add_recovery_action(recover_action2)

# Run the recovery plan and print result
result = recovery_plan.run_recovery_plan()
print(f"Recovery successful: {result}")
```

This example code defines a `RecoveryPlanner` class that can be used to manage error recovery actions in Python. The example includes two mock recovery functions, one of which will succeed, demonstrating how the planner can be extended and utilized in practice.