Bu

Built a Simple AI Code Reviewer in 3 Hours

Hacker News

Built a Simple AI Code Reviewer in 3 Hours

Hey HN, I spent a couple of hours this afternoon building a basic AI-powered code reviewer using Replit. Based on your custom instructions, it reviews code on existing pull requests and can even comment in your name. It’s still pretty simple, but it works! I’m honestly surprised at how quickly I got it up and running (took around 2-3 hours). Thought it’d be fun to share here in case anyone’s interested or has ideas for improvement. If you'd like to preview it: https://youtube.com/shorts/SmVabRsqZhw?feature=share Here’s the link if you want to check it out: http://ai-code-reviewer.replit.app/

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: using, code · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: reviews · Missing: plus, platform, intuitive
58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, code review · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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