Years ago, the author managed popular open-source projects on GitHub and faced challenges keeping up with issue management due to a busy schedule. To efficiently handle issues, a triage system using labels was implemented, but it proved tedious. This experience inspired the development of an automated triage tool using natural language processing (NLP) APIs like Recast.AI. The proposed solution involves creating a GitHub App to automate issue labeling by classifying issues as bugs, enhancements, or questions. The process includes training a language model with existing labeled issues from GitHub using a one-shot script and deploying a GitHub App to label new issues upon creation. The tool utilizes Recast.AI to analyze issue titles and classify them, following which a label is applied. The author provides a detailed guide on building this system, highlighting the challenges such as GitHub’s API rate limits and the benefits of expanding language support and data for improved accuracy. The project is open-source, encouraging others to build on it and share their developments.