During December 2025, Guangxi Yang developed a Reasoning Output Token Metrics feature for the DataDog/dd-trace-js repository, enhancing the OpenAI plugin’s ability to track token usage during reasoning tasks. He instrumented metric collection across multiple code paths and integrated the new metrics with existing reporting dashboards, using JavaScript and Node.js. Comprehensive unit and integration tests were added to ensure accurate capture and reporting of reasoning token metrics. This work improved observability and supported cost optimization for LLM-powered workflows. Guangxi Yang’s contribution demonstrated depth in API integration and full stack development, focusing on reliability and maintainability within a production monitoring context.