I released a OS remote agent callable from mobile

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Hey HN! I'm Emanuele (EmaDev01 on X), creator of FixO Dev, an open-source agent designed to instantly transform issues into high-quality pull requests. Today, I'm excited to officially launch it here! FixO Dev is perfect for quickly resolving small issues directly from GitHub, whether you're on your desktop, using your phone, or simply don't have your usual development environment available. Just mention @fixodev in any GitHub issue or PR comment, and watch it immediately generate professional-grade code fixes as pull requests. Check out the demo: https://youtu.be/NgGN2d2ZJLs As a developer, I often found myself needing quick, agile solutions for repetitive code improvements, especially when away from my main setup or working on-the-go. FixO Dev addresses this by delivering instant, secure, and effortless AI-driven fixes without leaving GitHub. With FixO Dev, you can: - Quickly resolve code issues directly from GitHub or even via mobile. - Trigger fixes simply by mentioning @fixodev. - Effortlessly handle multiple languages including JavaScript, TypeScript, Python, and more. - Rely on secure, isolated Docker-based execution without data retention. - Seamlessly integrate into open-source or enterprise workflows. Early users are leveraging FixO Dev to: - Swiftly automate small yet tedious code fixes. - Maintain high-quality, consistent codebases on-the-fly. Collaborate efficiently and reduce review overhead. I'm actively seeking feedback, community contributions, stars, and collaborations. Early adopters interested in private repository support are especially welcome. I'd love your thoughts—what small but repetitive coding tasks do you wish to solve instantly? Any ideas or feedback are highly appreciated!

Visit product View on Hacker NewsJun 22, 2025

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

95%95% 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 · Strong signals: including, efficiently · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: efficient, users · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

24%24% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: collaborate · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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