diff --git a/maxent.cabal b/maxent.cabal
--- a/maxent.cabal
+++ b/maxent.cabal
@@ -10,10 +10,10 @@
 -- PVP summary:      +-+------- breaking API changes
 --                   | | +----- non-breaking API additions
 --                   | | | +--- code changes with no API change
-version:             0.1.0.0
+version:             0.1.0.1
 
 -- A short (one-line) description of the package.
-synopsis:            Compute Maximum Entropy Distrubtions
+synopsis:            Compute Maximum Entropy Distributions
 
 -- A longer description of the package.
 description: Use this package to compute maximum entropy distributions given a list of values and
@@ -21,17 +21,21 @@
   .
   Here is a the example from Probability the Logic of Science 
   .
-   > maxent ([1,2,3], [average 1.5])
+  @
+    maxent ([1,2,3], [average 1.5])
+  @
   .
   Right [0.61, 0.26, 0.11]
   .
   The classic dice example
   .
-   > maxent ([1,2,3,4,5,6], [average 4.5])
+  @
+    maxent ([1,2,3,4,5,6], [average 4.5])
+  @
   .
   Right [.05, .07, 0.11, 0.16, 0.23, 0.34]
   
-  I will document this more ... soonish
+  
   
 -- URL for the project homepage or repository.
 homepage:            https://github.com/jfischoff/maxent
diff --git a/src/MaxEnt.hs b/src/MaxEnt.hs
--- a/src/MaxEnt.hs
+++ b/src/MaxEnt.hs
@@ -1,5 +1,13 @@
 -- |
--- Use this package to compute maximum entropy distributions given a list of values and
+-- The maximum entropy method, or MAXENT, is variational approach for computing probability 
+-- distributions given a list of moment, or expected value, constraints.
+-- 
+-- Here are a link for background info.
+-- On the idea of maximum entropy in general: 
+-- <http://en.wikipedia.org/wiki/Principle_of_maximum_entropy>
+--  
+-- 
+-- Use this package to compute discrete maximum entropy distributions over a list of values and
 -- list of constraints.
 -- 
 -- Here is a the example from Probability the Logic of Science
@@ -13,6 +21,14 @@
 -- > maxent ([1,2,3,4,5,6], [average 4.5])
 -- 
 -- Right [.05, .07, 0.11, 0.16, 0.23, 0.34]
+-- 
+-- One can use different constraints besides the average value there.  
+--
+-- As for why you want to maximize the entropy to find the probability constraint, 
+-- I will say this for now. In the case of the average constraint 
+-- it is a kin to choosing a integer partition with the most interger compositions. 
+-- I doubt that makes any sense, but I will try to explain more with a blog post soon.
+-- 
 module MaxEnt (
     Constraint,
     constraint,