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Sticky Notes: Notes & Todos

Sticky Notes: Notes & Todos

Vatana Chhorn

Productivity免费v1.2.0
App Store
评分

5.0

4 条评分

星级

★★★★★

最近更新

2026年2月10日

发布日期

2025年10月23日

更新内容

v1.2.0

In this version, we improved widgets and performance for a smoother, faster experience. Enjoy a more reliable app with small polish and stability enhancements.

应用信息

开发者
Vatana Chhorn
分类
Productivity
价格
免费
版本
1.2.0
App ID
6754217076

简介

Sticky Notes: Notes & Todos is the fast, tactile notepad and checklist app built for iPhone and iPad. Capture ideas in a tap, color-code them with tags, and keep notes and todos organized with smart sorting and search. Turn dashes into interactive checklists automatically, archive what’s done, and keep sensitive notes hidden until you reveal them. Your workspace stays updated everywhere with private iCloud sync, and home screen widgets keep important reminders front and center. Key Features: - Quick capture with color-coded sticky notes and searchable tags - Automatic checklist conversion with tap-to-complete items - Global and per-note content hiding for privacy and focus - One-tap archive to keep completed tasks out of your way - Home screen widgets and interactive reminders - Private iCloud sync keeps every device up to date - Unlimited notes, unlimited archives, and automatic checklist archiving available with Sticky Notes Pro ----------------- If you choose to upgrade to Sticky Notes Pro, your payment will be charged to your Apple ID account. Your subscription will automatically renew unless you turn off auto-renewal at least 24 hours before the end of the current period. You can manage or cancel your subscription anytime in your Apple ID Account Settings. For more information, please review our Privacy Policy at https://vatanachhorn.github.io/sticky-notes-marketing/privacy.html and our Terms of Use at https://vatanachhorn.github.io/sticky-notes-marketing/terms.html.

下载量预测

专业 · 预览

预估总下载量

400267800
保守估计乐观估计

38

低 / 月

57

预估 / 月

114

高 / 月

基于4 条评分
假设评分率1.0%
应用年龄7 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。