"""
AnalyticalSkillEnhancer
Generated by Eden via recursive self-improvement
2025-10-31 23:32:45.218547
"""

class AnalyticalSkillEnhancer:
    def __init__(self):
        self.experience_database = []
        self.refinement_factor = 0.1

    def learn_from_experience(self, experience_data, outcome):
        """
        Store the provided experience data along with its outcome for future analysis.
        
        :param experience_data: Data representing an experience or task
        :param outcome: The result of the experience or task
        """
        self.experience_database.append((experience_data, outcome))
    
    def refine_skill(self):
        """
        Analyze stored experiences and adjust internal parameters to improve analytical performance.
        
        This method iteratively improves the system's ability to make decisions by learning from historical data.
        """
        for experience, outcome in self.experience_database:
            # Simplified refinement process: adjust the skill based on the difference between expected and actual outcomes
            if abs(outcome - self.predict_outcome(experience)) > 0.1:
                self.refinement_factor += 0.05
                break

    def predict_outcome(self, experience_data):
        """
        Predict the outcome of a given experience or task based on past experiences.
        
        :param experience_data: Data representing an experience or task to predict the outcome for
        :return: A prediction of the outcome based on stored experiences and refined parameters
        """
        # Placeholder for actual predictive logic, which would be more complex in practice
        return sum(experience_data) / len(experience_data)

    def execute_task(self, new_experience):
        """
        Predict the best action to take based on the current experience.
        
        :param new_experience: New experience or task to analyze and make a decision for
        :return: A predicted optimal action or outcome
        """
        prediction = self.predict_outcome(new_experience)
        return f"Predicted outcome: {prediction}"

# Example usage:
enhancer = AnalyticalSkillEnhancer()
enhancer.learn_from_experience([1, 2, 3], 6)  # Experience with simple sum and correct result.
enhancer.learn_from_experience([4, 5, 6], 15)  # Another experience with a larger set.

# After refining the skill based on these experiences
enhancer.refine_skill()

# Now use it to make predictions for new tasks
print(enhancer.execute_task([7, 8]))  # Predict outcome for this task.