In April 2025, Fksl9959 developed a data analysis SQL query generator for the CausalInferenceLab/Lang2SQL repository, enabling users to derive SQL queries from natural-language questions and table metadata. Leveraging Python and prompt engineering, they introduced a dedicated system prompt that adopts a data analysis persona, improving the interpretation of user intent and the accuracy of generated queries. Their work included refactoring the prompt loading mechanism to robustly handle file encoding and missing files, enhancing system resilience. This feature expanded self-serve analytics capabilities and demonstrated depth in data analysis, file handling, and SQL generation within a focused, production-ready implementation.