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macOS Reminder Sync for Obsidian Tasks

Hacker News

macOS Reminder Sync for Obsidian Tasks

Greetings, I started using Obsidian and the brilliant Obsidian Tasks plugin to manage Tasks in my notes however it didn't quite work for me as I would lose track of Tasks when away from my laptop, and there are no reminders for Tasks so it's not easy to stay on top of things. I wrote my first macOS App to solve the problem; Reminder Sync for Obsidian. It periodically scans your Obsidian Vault for Tasks and creates Reminders for them in Reminders.app! Once your Tasks are created as Reminders they are synced through iCloud so they are also visible on iOS; this solves the main problem I had with Obsidian Tasks, allowing me to keep on top of Tasks with system Reminders and Widgets on macOS and iOS. Other features apart from the core functionality described above are: - Creating a Reminder adds a Task to an Inbox note in your Obsidian Vault, allowing you to create Obsidian Tasks from iOS. - Deleting/Completing a Task in Reminders app completes/deletes the Task in your Vault The core functionality is free, and I believe the free version should be sufficient for most users. Paid features include increased automatic sync frequency, ability to delete tasks from Reminders.app and ability to generate a description for the Reminder. The app is available on the App Store: https://apple.co/3TH1e5s You can view a demo video at the homepage: https://turquoisehexagon.co.uk/remindersync/ I would appreciate any feedback as it's my first solo App release!

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, started, ios · Missing: supports, reddit linkedin, podcasting
91%91% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, apple · Missing: agents, agent, cursor
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, video, users · Missing: mobile apps, personal, entrepreneurs
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
38%38% 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: users · 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
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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