In November 2024, Alberto Romero enhanced the stanfordnlp/dspy repository by developing comprehensive documentation focused on prompt optimization using G-Eval metrics. Leveraging Markdown and technical writing skills, he centralized external resources—including a Medium article, GitHub repository, and video tutorial—to streamline onboarding and knowledge sharing for prompt evaluation workflows. His work aligned documentation with evidence-based evaluation practices, supporting measurable improvements in prompt optimization and laying the foundation for future testing and QA processes. Although no bugs were fixed during this period, Alberto’s contributions improved the project’s maintainability and enabled faster iteration cycles by making advanced evaluation resources more accessible to developers.