Worked on the atcollab/at repository to enhance the reliability of data visualization in the acceptance workflow by addressing a critical bug in the plot_acceptance function. Focused on correcting the y-axis label assignment, the change ensured that acceptance plots accurately reflected their intended metrics, reducing the risk of misinterpretation for stakeholders relying on these visualizations. Utilized Python for both debugging and plotting, applying careful analysis to resolve a double-label assignment issue. Managed the update through Git-based workflows, emphasizing release hygiene and traceability. This targeted fix improved the accuracy of acceptance metrics and supported data-driven decisions across product and QA teams.