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Eden, explain the technical_debt_estimator_1765528437 capability
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This capability handles Quantifies and prioritizes technical debt remediation. Here's the implementation:

```python
import logging
from typing import Dict, List, Optional
from datetime import datetime

class TechnicalDebtEstimator:
    """
    Estimates and manages technical debt for code review systems.
    
    Attributes:
        project_name: Name of the project being analyzed
        issues_url: URL to Jira or GitHub issues
        logger: Logging instance for tracking activity
    """

    def __init__(self, project_name: str, issues_url: Optional[str] = None):
        """
        Initialize technical debt estimator.

        Args:
            project_name: Name of the project
            issues_url: Optional URL to issue tracker
        """
        self.project_name = project_name
        self.issues_url = issues_url
        self.logger = logging.getLogger(__name__)
        self._setup_logging()

    def _setup_logging(self) -> None:
        """
        Configure logging for the estimator.
        """
        logging.basicConfig(
            level=logging.INFO,
            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
        )

    def estimate_debt(self, code_review_data: Dict) -> float:
        """
        Estimate total technical debt points in the project.

        Args:
            code_review_data: Dictionary containing code review data

        Returns:
            Estimated total technical debt
        """
        try:
            self.logger.info("Estimating technical debt")
            
            # Extract relevant metrics from code review data
            PRs_count = code_review_data.get('PRs', {}).get('count', 0)
            issues_count = len(code_review_data.get('issues', []))
            
            # Calculate complexity-based points
            complexity_points = self._calculate_complexity_points(PRs_count, issues_count)

            # Estimate technical debt based on historical data and thresholds
            debt_estimate = max(0, (complexity_points * 1.2) - 50)
            
            return round(debt_estimate, 2)
        except E
```

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