Worked on improving the stability of the LMCache repository by addressing a critical issue in distributed tensor-parallel deployments. Using Python and leveraging expertise in distributed systems, error handling, and logging, implemented a fix for a crash caused by inconsistent hit tokens across parallel ranks. The solution introduced defensive logging and a safe fallback mechanism that selects the minimum hit token count when discrepancies occur, ensuring the system remains available and predictable under error conditions. This targeted bug fix reduced runtime errors and improved production reliability, demonstrating a methodical approach to maintaining uptime and robustness in complex distributed environments.