What is Auto Tagger?
Auto Tagger is an Obsidian plugin that automatically suggests tags for your notes based on your vault’s existing tagging patterns. It uses statistical analysis to learn which words are associated with which tags across your entire vault — no AI or external services required.Auto Tagger learns from your tagging habits. The more consistently you tag your notes, the better the suggestions become.
How It Works
Auto Tagger uses a four-stage process to suggest relevant tags:Vault Scan
On startup, the plugin scans all your notes and builds a statistical model of which words are associated with which tags.
TF-IDF Vectors
Each tag gets a weighted word profile using TF-IDF (Term Frequency-Inverse Document Frequency). Rare, distinctive words get more weight than common ones.
Cosine Similarity
When you open or edit a note, the plugin compares the note’s word vector against each tag’s profile using cosine similarity to find the best matches.
Key Features
Real-time Suggestions
Get tag suggestions as you type, with configurable debounce delay to avoid interruptions.
Multiple Trigger Methods
Suggestions appear when opening a note, while editing, or via command palette: “Suggest tags for current note”.
Flexible Tag Placement
Insert tags at the first line (inline), in frontmatter (YAML), or at the end of the current line.
Smart Filtering
Adjustable confidence threshold and max suggestions to control suggestion quality and quantity.
Interactive UI
Accept, skip, or dismiss suggestions one at a time, or view all suggestions in a modal dialog.
Multilingual Support
Supports both English and German content with built-in stopword filtering.
When to Use Auto Tagger
Auto Tagger is ideal for:- Large vaults with existing tagging patterns that you want to maintain consistency with
- Knowledge management workflows where tags help organize and retrieve information
- Personal wikis where you want to discover connections between notes through shared tags
- Research notes where consistent tagging helps track topics and themes