# Project Health Audit Report

This report provides a comprehensive overview of the health of your project, combining metrics for code complexity, code churn, and test coverage. It identifies areas that may require attention to improve maintainability, reduce risk, and enhance overall code quality.

## Project Information

* **Project Name:** `[Your Project Name Here]`
* **Repository Path:** `[Path to your repository, e.g., /Users/yourname/projects/my-project]`
* **Date Generated:** `[Date the report was generated, e.g., 2023-10-27]`

## Key Metrics Summary

| Metric          | Value       | Threshold      | Status     | Notes                                                                 |
|-----------------|-------------|----------------|------------|-----------------------------------------------------------------------|
| Cyclomatic Complexity (Avg) | `[Average Complexity]` | <= 10          | `[Good/Warning/Critical]` | Lower is better.  High complexity can indicate hard-to-understand code. |
| Code Churn (Avg Lines Changed/File) | `[Average Churn]` | <= 50          | `[Good/Warning/Critical]` | High churn can indicate areas of instability or frequent refactoring. |
| Test Coverage    | `[Coverage Percentage]` | >= 80%          | `[Good/Warning/Critical]` | Higher is better.  Low coverage increases the risk of undetected bugs. |
| Number of Files  | `[Total Files]` | N/A            | N/A        |  Provides context for the other metrics.                            |
| Number of Git Commits | `[Total Commits]` | N/A            | N/A        | Provides context for churn.                            |

**Status Legend:**

* **Good:** Metric is within acceptable range.
* **Warning:** Metric is approaching the threshold and may require investigation.
* **Critical:** Metric exceeds the threshold and requires immediate attention.

## Detailed Analysis

### 1. Code Complexity

This section analyzes the complexity of your code using Cyclomatic Complexity. Higher values indicate more complex code, which can be harder to understand, test, and maintain.

* **Files with Highest Complexity:**

    | File Path                         | Cyclomatic Complexity |
    |-----------------------------------|-----------------------|
    | `[Path to File 1]`                 | `[Complexity Value]`       |
    | `[Path to File 2]`                 | `[Complexity Value]`       |
    | `[Path to File 3]`                 | `[Complexity Value]`       |

    **Recommendations:** Refactor these files to reduce complexity. Consider breaking down large functions into smaller, more manageable units.  Use design patterns to simplify complex logic.

* **Average Complexity per Directory:**

    | Directory                         | Average Complexity |
    |-----------------------------------|-----------------------|
    | `[Path to Directory 1]`            | `[Average Value]`       |
    | `[Path to Directory 2]`            | `[Average Value]`       |

    **Recommendations:** Identify directories with high average complexity and prioritize refactoring efforts within those areas.

### 2. Code Churn

This section analyzes the frequency of changes (churn) in your codebase. High churn can indicate areas of instability or frequent refactoring.

* **Files with Highest Churn:**

    | File Path                         | Lines Changed (Total) | Number of Commits | Last Modified Date |
    |-----------------------------------|-----------------------|-------------------|--------------------|
    | `[Path to File 1]`                 | `[Lines Changed]`       | `[Commit Count]`    | `[Date]`            |
    | `[Path to File 2]`                 | `[Lines Changed]`       | `[Commit Count]`    | `[Date]`            |
    | `[Path to File 3]`                 | `[Lines Changed]`       | `[Commit Count]`    | `[Date]`            |

    **Recommendations:** Investigate files with high churn. Determine the reasons for frequent changes and consider refactoring or redesigning these areas. Look for patterns in the commits and identify potential root causes.

* **Areas with High Churn (Directories):**

    | Directory                         | Lines Changed (Total) | Number of Commits |
    |-----------------------------------|-----------------------|-------------------|
    | `[Path to Directory 1]`            | `[Lines Changed]`       | `[Commit Count]`    |
    | `[Path to Directory 2]`            | `[Lines Changed]`       | `[Commit Count]`    |

### 3. Test Coverage

This section analyzes the test coverage of your codebase. Low coverage increases the risk of undetected bugs.

* **Overall Test Coverage:** `[Coverage Percentage]`

* **Files with Low Coverage:**

    | File Path                         | Coverage Percentage |
    |-----------------------------------|-----------------------|
    | `[Path to File 1]`                 | `[Coverage Value]`       |
    | `[Path to File 2]`                 | `[Coverage Value]`       |
    | `[Path to File 3]`                 | `[Coverage Value]`       |

    **Recommendations:** Write unit tests for files with low coverage.  Focus on testing critical functionality and edge cases.  Consider using code coverage tools to identify untested code paths.

* **Areas with Low Coverage (Directories):**

    | Directory                         | Coverage Percentage |
    |-----------------------------------|-----------------------|
    | `[Path to Directory 1]`            | `[Coverage Value]`       |
    | `[Path to Directory 2]`            | `[Coverage Value]`       |

### 4. Combined Analysis & Recommendations

Based on the combined analysis of complexity, churn, and coverage, the following areas require the most urgent attention:

* `[File/Directory Name]` - High complexity, high churn, and low coverage.  Refactor and add tests.
* `[File/Directory Name]` - High complexity and low coverage. Refactor to reduce complexity, then add tests.
* `[File/Directory Name]` - High churn. Investigate the root cause of the frequent changes and consider redesign.

## Next Steps

1. Prioritize the areas identified in the "Combined Analysis & Recommendations" section.
2. Refactor complex code to improve readability and maintainability.
3. Write unit tests to increase test coverage and reduce the risk of bugs.
4. Investigate the reasons for high churn and address any underlying instability.
5. Run this report periodically to track progress and identify new areas for improvement.
