During January 2026, Wiley focused on enhancing data reliability in the BerriAI/litellm repository by addressing a bug related to API usage metrics. Wiley implemented a fallback mechanism in Python that derives the total_tokens value by summing input_tokens and output_tokens when the total_tokens field is missing. This approach improved the accuracy of usage analytics, billing, and quota enforcement, ensuring more dependable data processing for downstream systems. Wiley’s work demonstrated careful attention to maintainability and clear documentation, leveraging skills in API development and unit testing. The targeted fix delivered a low-risk, well-documented solution that strengthened the integrity of API usage data.