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Turnstile – a Windows browser picker that suggests routing rules

Hacker News

Turnstile – a Windows browser picker that suggests routing rules

Hi HN, I built Turnstile because I missed Choosy every time I used my Windows PC. I use multiple browsers on my Windows machine. Edge for work stuff, Firefox for personal browsing, and Chrome mostly for testing. This is not an unusual setup. But Windows makes you pick one default browser and that’s that. The problem starts when you click a link somewhere and it opens in the wrong one. Slack link? Should probably go to Edge since I’m signed into work accounts there. A YouTube link from WhatsApp? Firefox, because that’s where my personal Google account is. I got tired of copying links, switching browsers, and pasting them. So I built Turnstile. Turnstile registers itself as your default browser. When you click a link anywhere on the system, a small popup appears near your cursor with your installed browsers and profiles. Each one has a number next to it. Press the number and the link opens there. Press Escape and nothing happens. It can also skip the picker entirely using rules. Rules can match domains, regexes, or the application that opened the link. This is the part that made it useful for me: Turnstile suggests rules from actual usage. I realized I never really configured routing rules in Choosy because it was still a separate chore. Turnstile watches what you pick locally, and after a few consistent choices it asks something like: “You opened slack.com in Edge 12 out of 13 times. Create a rule?” If you accept, future matching links go there automatically. A few details: - WPF / .NET 9 - built with OpenCode and Codex as coding agents - no background service; it only runs when Windows invokes it as the default browser - config and usage data stay in %LOCALAPPDATA%\Turnstile - source-app detection uses Windows process APIs/P/Invoke because Windows does not directly tell the browser who launched the URL The basic picker and browser-profile support are free. Automation rules and smart suggestions are Pro, with a 30-day trial through the Microsoft Store. I’d especially like feedback from people who use multiple browsers or profiles every day. What routing rules would you expect? And are there Windows apps where source-app detection fails? You can read more about it on my blog: https://blog.perryizgr8.com/projects/2026/05/03/turnstile.ht... The app home page: https://turnstile.perryizgr8.com/ Get it from Microsoft Store: https://apps.microsoft.com/detail/9NTGZ68KK1X3

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agents, agent · Missing: macos, claude, model
80%80% 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: para · Missing: supports, reddit linkedin, podcasting
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, apps, google · Missing: mobile apps, ios, entrepreneurs
51%51% predicted probability of success on TrustMRR, 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
43%43% 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 · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · 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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