In May 2025, Sakib Akter developed a feature for the NVIDIA/NeMo-Skills repository focused on enhancing model response parsing with token probability logging. Using Python and leveraging backend development and API integration skills, Sakib extended the parse_openai_response workflow to accept and propagate a top_logprobs argument, enabling detailed token-level probability analysis. This addition improved observability and debugging by capturing granular log probability data for each generated token, supporting more effective model tuning and quality control. The work demonstrated a focused approach to deepening output analysis, with full traceability maintained through precise commit documentation and integration into the existing response pipeline.