Continuous scanning: Analyzes all new HN posts from accounts with <100 karma, scoring them for technical merit, originality, and problem-solving value AI curation: Every 12 hours, an LLM deep-dives into the top 10 candidates, checking GitHub repos, documentation quality, and actual utility
The result is what you see at the link - a curated list of overlooked quality posts that deserve more attention. The interesting part: I barely wrote any criteria. I just told Claude "open source good, pure commercial bad, working demos good" and let it figure out the scoring. The AI assessment varies slightly each run, which actually makes it more interesting. GitHub: https://github.com/DG1001/hn-gems
Is this useful? Do you have ideas how to improve this tool if necessary?
(And yes, my XaresAICoder that got 0 votes? The AI thinks it's actually pretty good. I'll take that as a win.)
