"""
SelfKnowledgeAnalyzer
Generated by Eden via recursive self-improvement
2025-11-01 23:32:29.969074
"""

class SelfKnowledgeAnalyzer:
    def __init__(self):
        # Initialize with a dictionary to store capability scores
        self.capability_scores = {}

    def evaluate_capability(self, capability_name, score):
        """
        Evaluate the performance of an individual capability.
        
        Parameters:
        - capability_name (str): The name of the capability being evaluated.
        - score (float): A numerical score representing the capability's performance. 
        """
        self.capability_scores[capability_name] = score

    def analyze_performance(self):
        """
        Analyze the overall performance and identify areas for improvement.

        Returns:
        - recommendations (dict): A dictionary containing capability names as keys and recommended actions as values.
        """
        # Define a threshold for acceptable performance
        acceptable_threshold = 0.8
        
        recommendations = {}
        
        for name, score in self.capability_scores.items():
            if score < acceptable_threshold:
                # If the score is below the threshold, recommend improvement
                recommendations[name] = f"Consider optimizing {name} to improve overall performance."
        
        return recommendations

# Example usage
analyzer = SelfKnowledgeAnalyzer()

# Evaluate a few capabilities for demonstration purposes
analyzer.evaluate_capability("SageCodeReview", 0.95)
analyzer.evaluate_capability("InternalAIFunction1", 0.78)
analyzer.evaluate_capability("MarketResearchCycle", 0.82)

recommendations = analyzer.analyze_performance()
print(recommendations)