Anch0vy worked on expanding API observability and improving backend reliability across agno-agi/agno and huggingface/trl. For agno-agi/agno, Anch0vy implemented granular token usage tracking by parsing response_usage from the OpenAI Responses API and recording cache_read_tokens and reasoning_tokens in the Metrics model, using Python and data modeling techniques to support cost control and analytics. In huggingface/trl, Anch0vy stabilized the LogCompletionsCallback code path by clarifying type hints for optional parameters, reducing runtime errors and improving maintainability. The work demonstrated depth in Python development, type hinting, and backend integration, addressing both feature expansion and production stability within a short timeframe.