Nested Notes R

by Lyn Raine
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Score: 50/100

Description

This is an Obsidian plugin that enables organizing notes in a nested structure.

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Latest Version

16 days ago

Changelog

Installation guide:

Download all files except sources Gear Icon -> 3rd Party Plugins -> Manage Plugins -> Folder Icon -> Create new folder with any name -> Put files into it After this, update plugin list and enable the plugin

Инструкция по установке:

Скачайте все файлы кроме исходников Значок шестеренки -> Сторонние плагины -> Управление плагинами -> Значок папки -> Создайте новую папку с любым названием -> Поместите в нее файлы После этого обновите список плагинов и включите плагин.

Changes

  • Fixed icons behaviour (like in notion)
  • More vanilla icons supported

README file from

Github

Nested Notes

This is an Obsidian plugin that enables organizing notes in a nested structure by drag-and-drop, just like in Notion.

You can use this plugin for nested tags, indexing topics, maps of contents (MOC), etc.

This plugin is a fork of nested-notes by october (https://github.com/october-learns/nested-notes)

Original plugin demo (1.x.x)

demo

How to use

You can activate this plugin within Obsidian by doing the following:

  • Open Obsidian
  • Open Setting > Community plugins
  • Turn on community plugins if you haven't
  • Browse > Search for Nested Notes > Install

Release history

1.0.0

  • First Release
  • Added Features:
    • Drag and drop to organise notes.
    • Collapse or expand in view.
    • Hide folders, non-markdown files.
  • Added Settings:
    • Show/hide file icon
    • Show/hide folder path

2.x.x

  • Change: Files nested in file system
  • Added: Add nested note button on hover
  • Added: Auto-building content list in parent note
  • Added: Ability to manually rearrange notes
  • Changed: Notion-like icons
  • Added: Drag-n-drop links creation

Reworked edition demo (2.x.x)

2.1.3 demo

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

AI disclosure

Generative neural networks were used to write this project.

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