diff --git a/README.md b/README.md
index fc0104c..318a576 100644
--- a/README.md
+++ b/README.md
@@ -3,7 +3,7 @@
 An on-device AI plugin for Joplin that semantically clusters notes, suggests tags and notebook structures, and detects stale/archivable notes.
 
 > [!NOTE]
-> This plugin is under active development as part of GSoC 2026. The initial embedding pipeline is implemented; clustering and UI panels are upcoming features.
+> This plugin is under active development as part of GSoC 2026. The embedding pipeline, clustering (K-Means, K-Medoids, HDBSCAN), and an interactive UI panel are implemented. Settings customization and staleness analysis are upcoming features.
 
 ---
 
@@ -25,6 +25,16 @@ The plugin implements a background-threaded embedding pipeline:
   * **Windows & macOS**: Automatically detects WebGPU support (`navigator.gpu`) and executes the model in **`fp16`** precision (at ~43ms per note).
   * **Linux (Fallback)**: Defaults to running on the CPU using WebAssembly (**`q8`** quantized precision, running ~2x faster than the standard `fp32` CPU baseline).
 
+## Current Features
+
+- **Embedding Pipeline**: On-device embedding generation with WebGPU acceleration and WASM fallback
+- **Native AI Integration**: Automatically uses Joplin's built-in AI Search embeddings when available
+- **Multi-Strategy Clustering**: Compare K-Means, K-Medoids, and HDBSCAN results side-by-side
+- **Interactive Panel**: Drag-and-drop notes between clusters, rename clusters, add custom categories
+- **Apply Categorization**: Organize notes into notebooks and/or tags based on clustering results
+- **Undo Support**: Revert any applied categorization with full change tracking
+- **Empty Notebook Cleanup**: Remove empty notebooks left after reorganization
+
 ---
 
 ## How to Run & Build
@@ -54,4 +64,5 @@ This script does the following:
 1. Open Joplin.
 2. Go to **Settings -> Plugins -> Manage Plugins -> Install from File** and select the `.jpl` package generated in `publish/`.
 3. Restart Joplin.
-4. Run the debug test from **Tools -> AI Categorise: Test Embedding**. This will index your local notes, run the tokenizer chunking, and output performance metrics directly to your developer tools console.
+4. Open the categorization panel from **View -> AI Categorise: Toggle Panel** (or click the brain icon on the note toolbar).
+5. Click **Analyse Notes** to run the full pipeline: notes are embedded, clustered, and results are displayed in the panel.
diff --git a/src/index.ts b/src/index.ts
index 18577de..7c4f940 100644
--- a/src/index.ts
+++ b/src/index.ts
@@ -170,7 +170,6 @@ joplin.plugins.register({
 			ToolbarButtonLocation.NoteToolbar,
 		);
 
-		log('Test command registered under Tools menu');
 		log('Panel registered');
 	},
 });
diff --git a/src/webview/pages/SettingsPage.tsx b/src/webview/pages/SettingsPage.tsx
index 4b04715..d554109 100644
--- a/src/webview/pages/SettingsPage.tsx
+++ b/src/webview/pages/SettingsPage.tsx
@@ -10,7 +10,7 @@ export const SettingsPage: React.FC = () => {
 			<div className="config-card">
 				<div className="config-card-header">Default Configuration:</div>
 				<div className="config-card-item">
-					• <strong>Model:</strong> ONNX BGE-Micro-v2
+					• <strong>Model:</strong> Xenova/all-MiniLM-L6-v2 (384-dim)
 				</div>
 				<div className="config-card-item">
 					• <strong>Metric:</strong> Cosine Similarity