diff --git a/orx-hash-grid/src/jvmDemo/kotlin/DemoFilter01.kt b/orx-hash-grid/src/jvmDemo/kotlin/DemoFilter01.kt
index 578238be..188f5cd4 100644
--- a/orx-hash-grid/src/jvmDemo/kotlin/DemoFilter01.kt
+++ b/orx-hash-grid/src/jvmDemo/kotlin/DemoFilter01.kt
@@ -9,6 +9,8 @@ import kotlin.random.Random
  * - Generates 10,000 random points uniformly distributed within the drawable bounds.
  * - Filters the generated points to enforce a minimum distance of 20.0 units between them.
  * - Visualizes the filtered points as circles with a radius of 10.0 units on the canvas.
+ *
+ * The `filter` method is provided by `orx-hash-grid`.
  */
 fun main() = application {
     configure {
diff --git a/orx-hash-grid/src/jvmDemo/kotlin/DemoFilter3D01.kt b/orx-hash-grid/src/jvmDemo/kotlin/DemoFilter3D01.kt
index 192ea0ba..5713bba4 100644
--- a/orx-hash-grid/src/jvmDemo/kotlin/DemoFilter3D01.kt
+++ b/orx-hash-grid/src/jvmDemo/kotlin/DemoFilter3D01.kt
@@ -11,10 +11,11 @@ import org.openrndr.math.Vector3
 import kotlin.random.Random
 
 /**
- * This demo sets up and renders a 3D visualization of filtered random points displayed as small spheres.
+ * Demonstrates how to use a 3D hash-grid `filter` operation to remove points from a random 3D point-collection
+ * that are too close to each other. The resulting points are displayed as small spheres.
  *
  * The program performs the following key steps:
- * - Generates 10,000 random 3D points within a ring defined by a minimum and maximum radius.
+ * - Generates 10,000 random 3D points located between a minimum and maximum radius.
  * - Filters the points to ensure a minimum distance between any two points using a spatial hash grid.
  * - Creates a small sphere mesh that will be instanced for each filtered point.
  * - Sets up an orbital camera to allow viewing the 3D scene interactively.
diff --git a/orx-hash-grid/src/jvmDemo/kotlin/DemoHashGrid01.kt b/orx-hash-grid/src/jvmDemo/kotlin/DemoHashGrid01.kt
index 39ecc382..45d8be0e 100644
--- a/orx-hash-grid/src/jvmDemo/kotlin/DemoHashGrid01.kt
+++ b/orx-hash-grid/src/jvmDemo/kotlin/DemoHashGrid01.kt
@@ -5,13 +5,15 @@ import org.openrndr.extra.noise.shapes.uniform
 import kotlin.random.Random
 
 /**
- * This demo sets up an interactive graphics application with a configurable
- * display window and visualization logic. It uses a `HashGrid` to manage points
- * in a 2D space and randomly generates points within the drawable area. These
- * points are then inserted into the grid if they satisfy certain spatial conditions.
+ * This demo creates a `HashGrid` to manage points in a 2D space.
+ * Notice the desired cell size in the HashGrid constructor.
+ *
+ * On every animation frame, it attempts to insert 100 random points into the HashGrid.
+ * When a HashGrid cell is free, a point is inserted.
+ *
  * The visual output includes:
- * - Rectangles representing the bounds of the cells in the grid.
- * - Circles representing the generated points.
+ * - Rectangles representing the bounds of the occupied cells in the grid.
+ * - Circles representing the generated random points.
  */
 fun main() = application {
     configure {
@@ -33,7 +35,6 @@ fun main() = application {
             drawer.fill = null
             drawer.stroke = ColorRGBa.WHITE
             drawer.rectangles(hashGrid.cells().map { it.bounds }.toList())
-            drawer.fill = null
             drawer.stroke = ColorRGBa.PINK
             drawer.circles(hashGrid.points().map { it.first }.toList(), 36.0)
         }