What is ai-topic-scout?

AI Topic Scout is a Codex skill built for AI creators, bloggers, and newsletter writers who need a steady stream of topic ideas drawn from reliable AI news sources. Instead of manually checking dozens of sites, you install this skill into Codex and it scans a fixed set of ten source types on your behalf. The sources it watches include OpenAI News, Anthropic News, Google DeepMind Blog, Meta AI Blog, Microsoft Research Blog, arXiv listings for AI, machine learning, and NLP, Hugging Face Papers, GitHub Trending, the LM Arena Leaderboard, and The Batch newsletter from DeepLearning.AI. It checks that items are current, removes duplicate stories, and turns the strongest signals into ideas ready for a creator to use, each with a suggested angle, a content format, links back to the source, and a priority ranking. The skill converts raw AI news into topic ideas written in Chinese, aimed at Chinese-language AI content creators. By default it returns eight to twelve ideas per run, and each one comes with several labeled fields covering the topic itself, why it matters now, a content angle, a suitable format, the source material, and a priority score. The output ends with a section naming the single best pick of the day, or up to three if there are several strong options. To install it, you use Codex's built-in skill installer and point it at the GitHub repository, or you can copy the skill folder manually into your local Codex skills directory and restart Codex so it picks up the new skill. Once installed, you call it by name inside Codex, for example asking it to produce today's topic list, scan the past week for short video friendly ideas, or pull tutorial topics from recent papers and GitHub trends. The repository itself is small, containing a SKILL.md file, an agent configuration file, and a references file listing the tracked sources. It is licensed under MIT.