During April 2026, Gupta enhanced rubric-based evaluation in the google/adk-python repository by enabling assessment of the full agent response, including all intermediate text generated during a single invocation. This feature, implemented in Python, introduced an option to include intermediate outputs alongside the final result, allowing for more comprehensive evaluation of multi-step tool interactions. By adding the evaluate_full_response option and a dedicated flag, Gupta improved the fidelity of benchmarking and feedback for evaluation systems. The work demonstrated depth in backend and API development, aligning closely with project goals and providing clearer traceability for evaluating agents that produce complex, staged outputs.