During April 2026, Waxinz developed an API messaging standardization feature for the NousResearch/hermes-agent repository, focusing on improving caching efficiency and prefix matching. Using Python and leveraging skills in backend development and data formatting, Waxinz implemented logic to strip leading and trailing whitespace from system prompts and message content, while normalizing tool-call arguments into compact, sorted JSON. This approach enabled more consistent prefix matching across API calls and improved cache hit rates, all without altering the original conversation history. The work demonstrated a thoughtful application of caching strategies and API integration, resulting in a simpler and more maintainable messaging layer.