Fix typos and enhance README content

Improved clarity in the README.

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 Steven Jannette
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,10 +1,10 @@
 # kongruity
 
-kongruity pulls in the unstructured artifacts of the creative-engineering process -- to-dos, action items, agile tickets, Jira comment threads, Slack threads, retrospective notes -- and synthesizes them into semantically coherent, prioritized clusters ready for implementation planning.
+kongruity pulls in unstructured artifacts of the creative-engineering process -- to-dos, action items, agile tickets, Jira thread comments, Slack thread comments, retrospective notes -- and synthesizes them into semantically coherent, prioritized clusters that can be incorporated into implementation planning.
 
-In kongruity world, these artifacts are "sticky notes." A board full of them looks chaotic. With a click, an LLM analyzes their semantic meaning and groups them into thematic clusters, each with a descriptive header. 
+In kongruity world, the artifacts become "sticky notes." A board full of them looks chaotic. With a click, the LLM analyzes their semantic meaning and groups them into thematic clusters, each with a descriptive header. 
 
-An independent embedding-based evaluation scores clustering quality, so the output is data-backed. From there, teams can simply drag-and-rank clusters by implementation priority, turning noise into an actionable workflow.
+An independent embedding-based evaluation model scores clustering quality, so the output is qualitatively refined. From there, teams can drag-and-rank related task clusters by implementation priority - turning noise into an actionable workflow.
 
 ## How it works
 
@@ -14,9 +14,14 @@ An independent embedding-based evaluation scores clustering quality, so the outp
 4. **Validate** — Structural checks confirm every note is assigned to exactly one cluster, no clusters are empty, and labels are present.
 5. **Prioritize** — Clusters appear ranked and are drag-reorderable. Teams set implementation priority by dragging clusters into position.
 
-## Dev implementation note
+## Dev implementation notes 
 
-Developers may swap in other LLM SDKs/APIs and alter prompt syntax in `backend/services/clustering.service.js` to experiment with any model or platform.
+As of 03.04.2026, two of the above-described features are in the planning and implementation phase:
+
+1. **Ingestion** - The implementation goal is a system for easily tagging items/issues mentioned in Slack, Jira comments, etc. (similar to hashtagging), and running batch "pulls" of these tagged items into kongruity via REST API interface.
+2. **Prioritization** -- The final prioritization and planning stage will ultimately result in "pushing" these ordered items back **out** into Jira, Asana, Rally (etc.), for incorporation into Epic/Sprint workflows. 
+
+Also, developers may swap in other LLM SDKs/APIs and alter prompt syntax in `backend/services/clustering.service.js` to experiment with any model or platform of their choice.
 
 ## Prerequisites
 
@@ -144,3 +149,5 @@ This runs Vitest with jsdom. For watch mode during development:
 ```bash
 npm run test:watch
 ```
+
+

backend/services/embedding.service.js

@@ -13,7 +13,7 @@ export const embedNotes = async (notes) => {
 
   const response = await client.embed({
     input: texts,
-    model: "voyage-3-lite",
+    model: "voyage-3",
   });
 
   const embeddingMap = new Map();

frontend/src/components/stickies.tsx

@@ -109,6 +109,9 @@ const Stickies = () => {
                 <span className="cluster-rank" aria-label={`Priority ${group.rank}`}>
                   {group.rank}
                 </span>
+                {group.rank === 1 && (
+                  <span className="cluster-reorder-hint">Drag and drop to reorganize cluster priority</span>
+                )}
                 <h3 className="cluster-label">{group.label}</h3>
                 <span className="cluster-drag-handle" aria-hidden="true">⠿</span>
               </div>

frontend/src/styles/stickies.css

@@ -60,6 +60,14 @@
   flex-shrink: 0;
 }
 
+.cluster-reorder-hint {
+  font-size: 0.8em;
+  color: #9ca3af;
+  font-style: italic;
+  white-space: nowrap;
+  flex-shrink: 0;
+}
+
 .cluster-label {
   margin: 0;
   font-size: 1.2em;