Show HN: Prompt Fatigue CC status line – Know when to stop prompting (github.com)

A new tool called Prompt Fatigue has been introduced for Claude Code, enabling users to monitor their prompting efficiency by analyzing their interaction patterns throughout the day. It tracks energy levels in real-time, helping users identify moments of peak productivity and signaling when it's time to take a break based on stimulating metrics. The tool operates entirely offline, ensuring privacy while providing insights into user energy and prompt quality. This feature is significant for the AI/ML community as it offers a systematic approach to enhancing the user's interaction with language models, encouraging higher-quality prompts through auto-feedback on performance. It utilizes metrics such as prompt length, engagement (like "yes" or "ok" responses), and specificity to calculate an energy score reflecting the user's mental state. With detailed breakdowns of daily energy trends, users can optimize their prompting strategies, potentially leading to more efficient use of AI resources while reducing cognitive overload. This development not only enhances productivity but also introduces a novel way to interact and improve upon machine learning models.