diff --git a/packages/website/docs/Api/DistGeneric.mdx b/packages/website/docs/Api/DistGeneric.mdx
index e15f3477..247bb4b8 100644
--- a/packages/website/docs/Api/DistGeneric.mdx
+++ b/packages/website/docs/Api/DistGeneric.mdx
@@ -377,7 +377,11 @@ logScore: ({estimate: distribution, ?prior: distribution, answer: distribution|n
 **Examples**
 
 ```javascript
-Dist.logScore({estimate: normal(5, 2), answer: normal(4.5, 1.2), prior: normal(6,4)}); // returns -0.597.57
+Dist.logScore({
+  estimate: normal(5, 2),
+  answer: normal(4.5, 1.2),
+  prior: normal(6, 4),
+}); // returns -0.597.57
 ```
 
 ## Display
@@ -621,4 +625,4 @@ dotPow: (distributionLike, distributionLike) => distribution
 
 ```
 dotExp: (distributionLike, distributionLike) => distribution
-```
\ No newline at end of file
+```
diff --git a/packages/website/docs/Api/DistSampleSet.md b/packages/website/docs/Api/DistSampleSet.md
index 68e2e7a8..4da7fee5 100644
--- a/packages/website/docs/Api/DistSampleSet.md
+++ b/packages/website/docs/Api/DistSampleSet.md
@@ -10,16 +10,18 @@ Monte Carlo calculations typically result in sample set distributions.
 All regular distribution function work on sample set distributions. In addition, there are several functions that only work on sample set distributions.
 
 ### fromDist
+
 ```
 Sampleset.fromDist: (list<number>) => sampleSet
 ```
 
 ### fromList
+
 ```
 Sampleset.fromList: (list<number>) => sampleSet
 ```
 
-### fromFn  
+### fromFn
 
 ```
 Sampleset.fromFn: ((float) => number) => sampleSet
@@ -61,4 +63,4 @@ Sampleset.map3: (sampleSet, sampleSet, sampleSet, ((number, number, number) => n
 
 ```
 Sampleset.mapN: (list<sampleSet>, (list<sampleSet> => number)) => sampleSet
-```
\ No newline at end of file
+```
diff --git a/packages/website/docs/Api/Function.md b/packages/website/docs/Api/Function.md
index b1c53ea3..1c08bb8f 100644
--- a/packages/website/docs/Api/Function.md
+++ b/packages/website/docs/Api/Function.md
@@ -7,7 +7,7 @@ title: Function
 
 Adds metadata to a function of the input ranges. Works now for numeric and date inputs. This is useful when making formal predictions. It allows you to limit the domain that your prediction will be used and scored within.
 
-The one function that declarations currently have is that they impact plotting. If you ``declare`` a single-variable function within a specific range, this specific range will be plotted.
+The one function that declarations currently have is that they impact plotting. If you `declare` a single-variable function within a specific range, this specific range will be plotted.
 
 Declarations are currently experimental and will likely be removed or changed in the future.
 
@@ -24,4 +24,4 @@ Function.declare({
     {min: 30, max: 100}
   ]
 })
-```
\ No newline at end of file
+```