Worked on the confident-ai/deepeval repository to address a specific issue in the Knowledge Retention scoring logic. Implemented a targeted bug fix using Python, ensuring that when no knowledge retention verdicts are present, the function now returns a default score of 1.0 instead of 0. This adjustment improved the reliability of downstream data analysis and metric calculation by preventing misinterpretation of evaluation results in edge cases. The solution maintained compatibility with existing analytics and dashboards, followed established code patterns, and provided clear traceability through Git. Demonstrated a disciplined approach to bug isolation, clean patching, and adherence to project standards.