diff --git a/orx-hash-grid/README.md b/orx-hash-grid/README.md
index b3f26b68..1257c656 100644
--- a/orx-hash-grid/README.md
+++ b/orx-hash-grid/README.md
@@ -4,6 +4,8 @@ A 2D space partitioning for points.
 
 ## Usage
 
+`orx-hash-grid` provides the classes `HashGrid` and `Cell`, in most cases only `HashGrid` is used.
+
 Create a hash grid for a given radius. 
 ```kotlin
 val grid = HashGrid(radius)
@@ -27,6 +29,42 @@ for (point in grid.points()) {
     // do something with point
 }
 ```
+
+## Extensions to standard library
+
+`orx-hash-grid` provides short-hand extension functions to `List<Vector2>`
+
+<hr>
+
+```kotlin
+fun List<Vector2>.filter(radius: Double) : List<Vector2>
+ ``` 
+
+filters the points in the list such that only points with an inter-distance of `radius` remain.
+
+```kotlin
+val points = (0 until 10_000).map { drawer.bounds.uniform() }
+val filtered = points.filter(20.0)
+```
+
+<hr>
+
+```kotlin 
+fun List<Vector2>.hashGrid(radius: Double) : HashGrid
+```
+constructs a (mutable) `HashGrid` containing all points in the list.
+
+```kotlin
+val points = (0 until 10_000).map { drawer.bounds.uniform() }
+val hashGrid = points.hashGrid(20.0)
+```
+
+<hr>
+
+## References
+
+ * `orx-noise` uses `HashGrid` to generate Poisson distributed points. [Link](https://github.com/openrndr/orx/blob/master/orx-noise/src/commonMain/kotlin/PoissonDisk.kt)
+
 <!-- __demos__ -->
 ## Demos
 ### DemoFilter01