Worked on the pydantic/pydantic-ai repository to enhance Gemini API schema compatibility by implementing advanced JSON Schema features and addressing a key nesting bug. Leveraged Python and Pydantic to improve schema transformation, handle nullable types, and remove unsupported properties, resulting in more reliable and maintainable API definitions. Focused on robust data modeling and schema design, the work included comprehensive testing to ensure compliance and reduce runtime errors. By correcting nested argument handling, the changes prevented misinterpretation of nested models as separate tool calls, streamlining downstream integrations with Gemini-based tooling and improving the overall reliability of schema-driven workflows.