Contributed to the watertap-org/watertap repository by improving both technical documentation and cost modeling accuracy. Addressed a critical issue in the ultra-filtration costing model by correcting the default capital cost parameter, which enhanced the reliability of financial projections and reduced the risk of overestimation. Enhanced developer-facing documentation by adding Python import paths for unit models, refining report unit representations, and updating terminology to reflect current architecture. Leveraged skills in Python, YAML, and technical writing to streamline onboarding and support maintainability. Focused on data configuration and documentation, the work enabled clearer guidance and more accurate modeling for future development efforts.