diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 9cfb951..f642d45 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -45,8 +45,8 @@ source envs/dev/bin/activate
 
 Update extension in a working database with:
 
-* `ALTER EXTENSION crankshaft VERSION TO 'current';`
-  `ALTER EXTENSION crankshaft VERSION TO 'dev';`
+* `ALTER EXTENSION crankshaft UPDATE TO 'current';`
+  `ALTER EXTENSION crankshaft UPDATE TO 'dev';`
 
 Note: we keep the current development version install as 'dev' always;
 we update through the 'current' alias to allow changing the extension
@@ -58,7 +58,10 @@ should be dropped manually before the update.
 If the extension has not previously been installed in a database,
 it can be installed directly with:
 
-* `CREATE EXTENSION crankshaft WITH VERSION 'dev';`
+* `CREATE EXTENSION IF NOT EXISTS plpythonu;`
+  `CREATE EXTENSION IF NOT EXISTS postgis;`
+  `CREATE EXTENSION IF NOT EXISTS cartodb;`
+  `CREATE EXTENSION crankshaft WITH VERSION 'dev';`
 
 Note: the development extension uses the development python virtual
 environment automatically.
diff --git a/doc/02_moran.md b/doc/02_moran.md
index 85384cb..c91eb3f 100644
--- a/doc/02_moran.md
+++ b/doc/02_moran.md
@@ -1,4 +1,102 @@
-### Moran's I
+## Name
+
+CDB_AreasOfInterest -- returns a table with a cluster/outlier classification, the significance of a classification, an autocorrelation statistic (Local Moran's I), and the geometry id for each geometry in the original dataset.
+
+## Synopsis
+
+```sql
+table(numeric moran_val, text quadrant, numeric significance, int ids, numeric column_values) CDB_AreasOfInterest(text query, text column_name)
+
+table(numeric moran_val, text quadrant, numeric significance, int ids, numeric column_values) CDB_AreasOfInterest(text query, text column_name, int permutations, text geom_column, text id_column, text weight_type, int num_ngbrs)
+```
+
+## Description
+
+CDB_AreasOfInterest is a table-returning function that classifies the geometries in a table by an attribute and gives a significance for that classification. This information can be used to find "Areas of Interest" by using the correlation of a geometry's attribute with that of its neighbors. Areas can be clusters, outliers, or neither (depending on which significance value is used).
+
+Inputs:
+
+* `query` (required): an arbitrary query against tables you have access to (e.g., in your account, shared in your organization, or through the Data Observatory). This string must contain the following columns: an id `INT` (e.g., `cartodb_id`), geometry (e.g., `the_geom`), and the numeric attribute which is specified in `column_name`
+* `column_name` (required): column to perform the area of interest analysis tool on. The data must be numeric (e.g., `float`, `int`, etc.)
+* `permutations` (optional): used to calculate the significance of a classification. Defaults to 99, which is sufficient in most situations.
+* `geom_column` (optional): the name of the geometry column. Data must be of type `geometry`.
+* `id_column` (optional): the name of the id column (e.g., `cartodb_id`). Data must be of type `int` or `bigint` and have a unique condition on the data.
+* `weight_type` (optional): the type of weight used for determining what defines a neighborhood. Options are `knn` or `queen`.
+* `num_ngbrs` (optional): the number of neighbors in a neighborhood around a geometry. Only used if `knn` is chosen above.
+
+Outputs:
+
+* `moran_val`: underlying correlation statistic used in analysis
+* `quadrant`: human-readable interpretation of classification
+* `significance`: significance of classification (closer to 0 is more significant)
+* `ids`: id of original geometry (used for joining against original table if desired -- see examples)
+* `column_values`: original column values from `column_name`
+
+Availability: crankshaft v0.0.1 and above
+
+## Examples
+
+```sql
+SELECT
+  t.the_geom_webmercator,
+  t.cartodb_id,
+  aoi.significance,
+  aoi.quadrant As aoi_quadrant
+FROM
+  observatory.acs2013 As t
+JOIN
+  crankshaft.CDB_AreasOfInterest('SELECT * FROM observatory.acs2013',
+                                 'gini_index')
+```
+
+## API Usage
+
+Example
+
+```text
+http://eschbacher.cartodb.com/api/v2/sql?q=SELECT * FROM crankshaft.CDB_AreasOfInterest('SELECT * FROM observatory.acs2013','gini_index')
+```
+
+Result
+```json
+{
+  time: 0.120,
+  total_rows: 100,
+  rows: [{
+    moran_vals: 0.7213,
+    quadrant: 'High area',
+    significance: 0.03,
+    ids: 1,
+    column_value: 0.22
+  },
+  {
+    moran_vals: -0.7213,
+    quadrant: 'Low outlier',
+    significance: 0.13,
+    ids: 2,
+    column_value: 0.03
+  },
+  ...
+  ]
+}
+```
+
+## See Also
+
+crankshaft's areas of interest functions:
+
+* [CDB_AreasOfInterest_Global]()
+* [CDB_AreasOfInterest_Rate_Local]()
+* [CDB_AreasOfInterest_Rate_Global]()
+
+
+PostGIS clustering functions:
+
+* [ST_ClusterIntersecting](http://postgis.net/docs/manual-2.2/ST_ClusterIntersecting.html)
+* [ST_ClusterWithin](http://postgis.net/docs/manual-2.2/ST_ClusterWithin.html)
+
+
+-- removing below, working into above
 
 #### What is Moran's I and why is it significant for CartoDB?
 
diff --git a/doc/docs_template.md b/doc/docs_template.md
new file mode 100644
index 0000000..9d5b550
--- /dev/null
+++ b/doc/docs_template.md
@@ -0,0 +1,24 @@
+
+## Name
+
+## Synopsis
+
+## Description
+
+Availability: v...
+
+## Examples
+
+```SQL
+-- example of the function in use
+SELECT cdb_awesome_function(the_geom, 'total_pop')
+FROM table_name
+```
+
+## API Usage
+
+_asdf_
+
+## See Also
+
+_Other function pages_