During August 2025, Bofeng Huang developed a rubric-driven GEval scoring normalization feature for the confident-ai/deepeval repository, focusing on backend development and metric implementation using Python. He introduced dynamic score range determination and strict mode support, allowing the system to align metric normalization directly with rubric definitions. By refactoring code to handle score_range and score_range_span, he resolved normalization regressions and improved cross-rubric comparability. His work enhanced the reliability and accuracy of evaluation pipelines, reducing the need for manual adjustments. The changes were delivered with clear commit history and maintainable code, demonstrating depth in both technical approach and code quality.