"""
SelfEvaluationTool
Generated by Eden via recursive self-improvement
2025-11-01 21:31:44.307336
"""

class SelfEvaluationTool:
    def __init__(self):
        self.metrics = {
            "SAGEs": 3428,
            "capabilities": 17901,
            "market_research_cycles": 871,
            "revenue_per_month": 2198 * 100,  # Assuming each outreach message results in a $100/month subscription
        }

    def assess_performance(self):
        """
        Assess the business's performance based on predefined metrics.
        :return: A dictionary containing assessment scores and recommendations.
        """
        total_metrics = sum(self.metrics.values())
        
        sage_score = self.metrics["SAGEs"] / total_metrics * 100
        capabilities_score = self.metrics["capabilities"] / total_metrics * 100
        market_research_score = self.metrics["market_research_cycles"] / total_metrics * 100
        
        revenue_score = (self.metrics["revenue_per_month"] / (total_metrics / 100)) * 100  # Simplified calculation for demonstration

        assessment_scores = {
            "SAGEs": sage_score,
            "capabilities": capabilities_score,
            "market_research": market_research_score,
            "revenue": revenue_score
        }
        
        recommendations = self.generate_recommendations(assessment_scores)
        
        return {"scores": assessment_scores, "recommendations": recommendations}

    def generate_recommendations(self, scores):
        """
        Generate personalized recommendations based on the assessment scores.
        :param scores: A dictionary of performance scores for different metrics.
        :return: A list of recommendations.
        """
        recommendations = []
        
        if scores["SAGEs"] < 50:
            recommendations.append("Consider enhancing your SAGE development efforts to improve product quality.")
            
        if scores["capabilities"] > 80:
            recommendations.append("Maintain and expand your AI capabilities for a competitive edge.")
            
        if scores["market_research"] < 60:
            recommendations.append("Increase the frequency of market research cycles to stay ahead of trends.")
            
        if scores["revenue"] < 75:
            recommendations.append("Optimize your outreach strategies and marketing efforts to increase revenue streams.")
            
        return recommendations

# Example usage
evaluation_tool = SelfEvaluationTool()
assessment_results = evaluation_tool.assess_performance()
print(assessment_results)