Readme.ai – Turn Your GitHub Profile into a Beautiful

Hacker News

I built README.ai, a tool that transforms any public GitHub profile into a polished, professional README using AI. How it works: Enter your GitHub username It fetches your profile, pinned & top-starred repos, language stats Sends this data to an AI prompt (can be connected to OpenAI) Generates a personalized README with live preview Download and paste into your profile repo – done! Why? I noticed many devs (especially juniors) struggle to present themselves well on GitHub, despite having good work. I wanted to build something that made this effortless. Stack: React + Vite + Tailwind Shadcn UI components GitHub REST & GraphQL APIs react-markdown for preview Optional: OpenAI or other LLM backend No login. No data stored. Just works. I’d love feedback, feature suggestions, or just to hear what you think. Contributions welcome too. GitHub: https://github.com/mandarwagh9/readme.ai

Visit product View on Hacker NewsJun 21, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, openai, using · Missing: mac, agents, macos

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

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TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

16%16% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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