During January 2026, contributed to the Arize-ai/phoenix repository by stabilizing the evaluator pipeline through a targeted bug fix addressing input schema access for built-in evaluators. This work involved refining the instantiation and retrieval process of input schemas, which reduced runtime errors and improved the reliability of evaluator execution. Leveraging Python for backend development and API handling, the developer focused on debugging and refactoring schema management logic. The solution enhanced configuration workflows and maintainability by ensuring clear commit history and thorough validation of configuration flows, laying a stronger foundation for future enhancements to the evaluator system within the project.