Worked on the confident-ai/deepeval repository to enhance the reliability and maintainability of its evaluation pipeline, focusing on test integrity rather than feature development. Addressed a documentation issue by correcting an incorrect variable name in the Evaluation Arena Test Case Integrity, ensuring the proper ArenaGEval instance was referenced when printing test results. This change improved the accuracy and reproducibility of test outputs, aligning documentation with the underlying Python evaluation logic. The primary technical contribution centered on stabilizing the test harness, reducing risks in continuous integration pipelines, and supporting maintainable workflows through precise documentation and careful attention to test-case references and outcomes.