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DitchTheBell – Linux-based desktop notifier for RSS/Atom feeds

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DitchTheBell – Linux-based desktop notifier for RSS/Atom feeds

Ditch The Bell is a desktop notifier for RSS/Atom feeds that lets you closely configure features of the freedesktop notification specification to unlock the most customizable feed notification experience possible on Linux. I developed this program because I wanted a single, centralized location to easily manage my desktop notifications for all of the various websites I want to get updates from. Before creating this application, I found existing solutions unsatisfactory due to the following reasons: - Built-In Notification Services: Some websites offer built-in desktop notification services, but these often require an account, staying signed in, and running a browser service worker continuously on your PC. - RSS Readers: While existing RSS readers with notification support provide a simple solution, these project balance numerous aspects of reader development. Notifications and their configurations are usually not the priority in these projects. - Custom Scripting: Implementing custom scripts using general-purpose notification tools like notify-send or GObject-Introspection is viable but becomes a maintenance headache as more granular control is introduced. These alternatives are sufficient for basic notifications but lack the lightweight nature and advanced configurability that power users desire. Ditch The Bell fills this gap, offering granular control over your RSS feed notifications without the limitations of the approaches mentioned above. Check it out!: https://github.com/EscherMoore/DitchTheBell

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive
52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, single, using · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · 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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