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Tab Link

by jon-vii
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Description

This plugin has not been manually reviewed by Obsidian staff. Cursor-style ghost text autocomplete for linking to notes.

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Latest Version

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Changelog

See all version on GitHub

README file from

Github

Tab Link

GitHub release License: MIT

Ghost text autocomplete for wiki-links in Obsidian.

Tab Link Demo

Type naturally. When you start typing a note name, ghost text appears inline. Press Tab to accept and create the link.

Features

  • Ghost text, not popups — Non-intrusive inline suggestions that don't break your flow
  • Tab to accept — Fast keyboard-driven workflow
  • Smart context — Won't suggest inside existing links, code blocks, or frontmatter
  • Frecency scoring — Ranks suggestions by frequency + recency of use
  • Phrase matching — "mach learn" matches "Machine Learning"
  • Alias support — Searches frontmatter aliases alongside note titles
  • Auto-space — Optionally adds a space after accepting (configurable)

Installation

Using BRAT (recommended)

  1. Install BRAT from Community Plugins
  2. Open BRAT settings → Add Beta Plugin
  3. Enter: Jon-Vii/obsidian-tab-link
  4. Enable the plugin

Manual Installation

  1. Download the latest release from GitHub Releases
  2. Extract to <vault>/.obsidian/plugins/obsidian-tab-link/
  3. Enable in Settings → Community Plugins

Usage

  1. Start typing text that matches a note name (5+ characters by default)
  2. Ghost text appears showing the suggested completion
  3. Press Tab to accept → creates the link
  4. Press Escape or keep typing to dismiss
Key Action
Tab Accept suggestion
Escape Dismiss suggestion
Space Dismiss and continue typing
Arrow keys Dismiss suggestion

Settings

Setting Default Description
Enable ghost text On Toggle suggestions on/off
Auto-space after link On Add space after accepting a link
Minimum characters 5 Characters needed before suggestions appear (3-8)
Debounce delay 150ms Wait time after typing before showing suggestions
Excluded folders — Comma-separated folders to ignore

How It Works

  • Trie-based matching — O(k) prefix lookups where k = query length
  • Frecency scoring — Recently and frequently linked notes rank higher
  • Performance-conscious — Debounced updates, chunked indexing on startup

License

MIT

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