Nintang focused on enhancing the training visualization documentation within the thinking-machines-lab/tinker-cookbook repository, delivering a feature that clarifies the mapping between inputs, targets, and weights in the training process. By updating the training-sampling.mdx file using Markdown and leveraging skills in data visualization and technical writing, Nintang improved the documentation’s clarity and usability. The work addressed issue #182 and was committed in collaboration with John Schulman, demonstrating attention to code quality and collaborative workflows. This enhancement reduces ambiguity for new contributors and supports more effective onboarding, reflecting a thoughtful approach to documentation-driven engineering within a research-oriented codebase.