docs: sync org README with master — OpenRAL org, 31 rSkills, scene VLM query_scene (ADR-0047)

index.html

@@ -213,13 +213,13 @@
 
   <!-- Badges -->
   <div class="badges">
-    <a class="badge" href="https://github.com/AdrianLlopart/openral">⬛ GitHub</a>
+    <a class="badge" href="https://github.com/OpenRAL/openral">⬛ GitHub</a>
     <a class="badge" href="https://docs.openral.dev">📄 Docs</a>
     <a class="badge" href="https://discord.gg/ZdNyUT4V5">💬 Discord</a>
     <span class="badge">Apache-2.0</span>
     <span class="badge">ROS 2 Jazzy</span>
     <span class="badge">Python 3.12</span>
-    <span class="badge">16 robots · 20 rSkills · 22 benchmarks</span>
+    <span class="badge">16 robots · 31 rSkills · 22 benchmarks</span>
   </div>
 
   <!-- What is it -->
@@ -237,7 +237,7 @@
   <!-- Quick start -->
   <h2>Get started</h2>
   <pre><code># Install (no clone needed)
-curl -fsSL https://raw.githubusercontent.com/AdrianLlopart/openral/master/scripts/install.sh | bash
+curl -fsSL https://raw.githubusercontent.com/OpenRAL/openral/master/scripts/install.sh | bash
 openral doctor
 
 # Browse and install a skill
@@ -309,8 +309,9 @@ openral deploy run --config deployments/so100_pickplace.yaml</code></pre>
     <table>
       <thead><tr><th>Type</th><th>What</th><th>Count</th></tr></thead>
       <tbody>
-        <tr><td><code>rskill-*</code> models</td><td>Policy rSkills — VLA weights + manifest + eval</td><td>19</td></tr>
-        <tr><td><code>rskill-*</code> models</td><td>Perception rSkills — RT-DETR object-detection</td><td>4</td></tr>
+        <tr><td><code>rskill-*</code> models</td><td>Policy rSkills — VLA weights + ROS-wrapped action skills + manifest + eval</td><td>27</td></tr>
+        <tr><td><code>rskill-*</code> models</td><td>Perception detector rSkills — RT-DETR + LocateAnything → <code>ObjectsMetadata</code></td><td>3</td></tr>
+        <tr><td><code>rskill-*</code> models</td><td>Scene-understanding VLM rSkill (<code>kind: vlm</code>) — drives the reasoner's read-only <code>query_scene</code> tool</td><td>1</td></tr>
         <tr><td><code>dataset-*</code></td><td>LeRobotDataset v3 demonstration datasets</td><td>growing</td></tr>
       </tbody>
     </table>
@@ -318,7 +319,7 @@ openral deploy run --config deployments/so100_pickplace.yaml</code></pre>
 
   <!-- rSkills -->
   <h2>Policy rSkills</h2>
-  <p>Each rSkill is a self-contained Hub repo: <code>rskill.yaml</code> manifest, <code>model.safetensors</code> weights, <code>eval/</code> results, and a model card with runnable examples. Install with <code>openral rskill install OpenRAL/rskill-&lt;name&gt;</code>.</p>
+  <p>Each rSkill is a self-contained Hub repo: <code>rskill.yaml</code> manifest, <code>model.safetensors</code> weights, <code>eval/</code> results, and a model card with runnable examples. Install with <code>openral rskill install OpenRAL/rskill-&lt;name&gt;</code>. The table below shows a representative subset of the 27 policy rSkills (VLA + ROS-wrapped action skills).</p>
 
   <div class="table-wrap">
     <table>
@@ -415,16 +416,16 @@ openral deploy run --config deployments/so100_pickplace.yaml</code></pre>
           <td><span class="lic lic-red"></span>RLWRLD non-commercial</td>
         </tr>
         <tr>
-          <td><code>rskill-gr00t-libero-nf4</code></td>
-          <td>Gr00t N1.7</td><td>Franka Panda</td>
+          <td><code>rskill-gr00t-n17-libero</code></td>
+          <td>GR00T N1.7</td><td>Franka Panda</td>
           <td><span class="lic lic-green"></span>NVIDIA Open Model</td>
         </tr>
       </tbody>
     </table>
   </div>
 
-  <h2>Perception rSkills</h2>
-  <p>Emit <code>ObjectsMetadata</code> (2D detections lifted to 3D via depth) rather than an <code>Action</code>. Plug directly into the <code>openral deploy</code> graph.</p>
+  <h2>Perception detector rSkills</h2>
+  <p><code>kind: detector</code> — emit <code>ObjectsMetadata</code> (2D detections lifted to 3D via depth) rather than an <code>Action</code>. Plug directly into the <code>openral deploy</code> graph and fold into World State.</p>
   <div class="table-wrap">
     <table>
       <thead><tr><th>rSkill</th><th>Backbone</th><th>Notes</th><th>License</th></tr></thead>
@@ -440,14 +441,24 @@ openral deploy run --config deployments/so100_pickplace.yaml</code></pre>
           <td><span class="lic lic-green"></span>Apache-2.0</td>
         </tr>
         <tr>
-          <td><code>rskill-qwen35-4b-nf4</code></td>
-          <td>Qwen3.5-4B</td><td>Scene Understanding</td>
-          <td><span class="lic lic-green"></span>Apache-2.0</td>
+          <td><code>rskill-locateanything-3b-nf4</code></td>
+          <td>LocateAnything-3B</td><td>Open vocabulary (out-of-process NF4 sidecar)</td>
+          <td><span class="lic lic-red"></span>NVIDIA non-commercial</td>
         </tr>
+      </tbody>
+    </table>
+  </div>
+
+  <h2>Scene-understanding VLM rSkill</h2>
+  <p><code>kind: vlm</code> — a scene VLM that answers open-ended questions about the current view. It powers the S2 reasoner's <strong>read-only</strong> <code>query_scene</code> tool for task-progress / success verification ("did the grasp succeed?"); it holds no actuation authority (ADR-0047). Runs out-of-process in an NF4 sidecar served by <code>scene_vlm_node</code>.</p>
+  <div class="table-wrap">
+    <table>
+      <thead><tr><th>rSkill</th><th>Backbone</th><th>Notes</th><th>License</th></tr></thead>
+      <tbody>
         <tr>
-          <td><code>`rskill-locateanything-3b-nf4</code></td>
-          <td>LocateAnything-3B</td><td>Open Vocabulary</td>
-          <td><span class="lic lic-red"></span>NVIDIA non-commercial</td>
+          <td><code>rskill-qwen35-4b-nf4</code></td>
+          <td>Qwen3.5-4B NF4 (~2.5 GB)</td><td>Reasoner <code>query_scene</code> tool · role <code>s2</code></td>
+          <td><span class="lic lic-green"></span>Apache-2.0</td>
         </tr>
       </tbody>
     </table>
@@ -532,7 +543,7 @@ openral benchmark report</code></pre>
 
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