Worked on enhancing the vellum-ai/vellum-python-sdks repository by introducing a targeted configurability feature to improve data exposure controls during code generation. Developed and integrated the maskIndexingConfig query parameter, allowing users to control the masking of indexing configuration when generating code. This update involved modifying the TextSearchNodeContext to support finer-grained information exposure, addressing privacy and compliance needs while ensuring compatibility with existing workflows. Leveraged TypeScript for backend development and API integration, focusing on parameterized configuration propagation and assessing the end-to-end impact across the codebase. The work emphasized robust, privacy-aware codegen tooling without introducing breaking changes or regressions.