Updated README

Author: rjrudin

README.md

@@ -7,23 +7,23 @@ ml-app-deployer is a Java library that provides two capabilities:
 1. A client library for the new [Management REST API](http://docs.marklogic.com/REST/management) in MarkLogic 8. 
 1. A command-driven approach for deploying and undeploying an application to MarkLogic that depends on the management client library.
 
-If you're just looking for a Java library for interacting with the Management REST API, you can certainly use ml-app-deployer. The deployer/command library is mostly a thin layer around the management client library and can be safely ignored if you don't need it. 
-
-Javadocs for ml-app-deployer are [here](http://rjrudin.github.io/marklogic-java/javadocs/ml-app-deployer/index.html).
+If you're just looking for a Java library for interacting with the Management REST API, you can certainly use ml-app-deployer. 
+The deployer/command library is mostly a thin layer around the management client library and can be safely ignored if you don't need it. 
 
 ### What does ml-app-deployer depend on? 
 
 ml-app-deployer depends on MarkLogic 8 and Java 1.7+.
 
-Under the hood, it depends on Spring's [RestTemplate](http://docs.spring.io/spring/docs/current/javadoc-api/org/springframework/web/client/RestTemplate.html) for interacting with the Management REST API. It also depends on [ml-javaclient-util](https://github.com/rjrudin/ml-javaclient-util) for loading modules, which is done via the MarkLogic Client REST API. 
+Under the hood, it depends on Spring's [RestTemplate](http://docs.spring.io/spring/docs/current/javadoc-api/org/springframework/web/client/RestTemplate.html) for interacting with the Management REST API. 
+It also depends on [ml-javaclient-util](https://github.com/marklogic-community/ml-javaclient-util) for loading modules, which is done via the MarkLogic Client REST API. 
 
 ### How do I start using the client library?
 
 The general pattern for using the management client library is:
 
-1. Create an instance of [ManageConfig](https://github.com/rjrudin/ml-app-deployer/blob/master/src/main/java/com/marklogic/mgmt/ManageConfig.java), which specifies connection information for the management REST API instance.
-2. Create an instance of [ManageClient](https://github.com/rjrudin/ml-app-deployer/blob/master/src/main/java/com/marklogic/mgmt/ManageClient.java) using ManageConfig. ManageClient simply wraps a RestTemplate with some convenience methods.
-3. Using ManageClient, create a Manager class based on the management resource you want to configure. For example, to create or modify or delete a database, create a [DatabaseManager](https://github.com/rjrudin/ml-app-deployer/blob/master/src/main/java/com/marklogic/mgmt/databases/DatabaseManager.java) to talk to the [database endpoints](http://docs.marklogic.com/REST/management/databases). 
+1. Create an instance of [ManageConfig](https://github.com/marklogic-community/ml-app-deployer/blob/master/src/main/java/com/marklogic/mgmt/ManageConfig.java), which specifies connection information for the management REST API instance.
+2. Create an instance of [ManageClient](https://github.com/marklogic-community/ml-app-deployer/blob/master/src/main/java/com/marklogic/mgmt/ManageClient.java) using ManageConfig. ManageClient simply wraps a RestTemplate with some convenience methods.
+3. Using ManageClient, create a Manager class based on the management resource you want to configure. For example, to create or modify or delete a database, create a [DatabaseManager](https://github.com/marklogic-community/ml-app-deployer/blob/master/src/main/java/com/marklogic/mgmt/databases/DatabaseManager.java) to talk to the [database endpoints](http://docs.marklogic.com/REST/management/databases). 
 
 Here's a brief example of what that looks like:
 
@@ -36,7 +36,7 @@ Here's a brief example of what that looks like:
 
 The main concept behind the deployer library is invoke a series of commands, where each command looks for one or more configuration files in a specific directory structure and then uses a Manager class in the client library to apply those configuration files as part of deploying an application. 
 
-The best way to understand that directory is to look at the [sample-app application](https://github.com/rjrudin/ml-app-deployer/tree/master/src/test/resources/sample-app/src/main/ml-config) that's used by the JUnit tests. The concept is fairly simple - within the ml-config directory, there's a directory for each of the top-level resources defined by the [Management API docs](http://docs.marklogic.com/REST/management). Thus, database config files are found under "databases", while scheduled task config files are found under "scheduled-tasks". Some directories have subdirectories based on how the Management API endpoints are defined - for example, the "security" directory has child directories of "amps", "roles", "users", and others based on the resources that comprise the "security" set of endpoints. 
+The best way to understand that directory is to look at the [sample-app application](https://github.com/marklogic-community/ml-app-deployer/tree/master/src/test/resources/sample-app/src/main/ml-config) that's used by the JUnit tests. The concept is fairly simple - within the ml-config directory, there's a directory for each of the top-level resources defined by the [Management API docs](http://docs.marklogic.com/REST/management). Thus, database config files are found under "databases", while scheduled task config files are found under "scheduled-tasks". Some directories have subdirectories based on how the Management API endpoints are defined - for example, the "security" directory has child directories of "amps", "roles", "users", and others based on the resources that comprise the "security" set of endpoints. 
 
 The logic for when to look for files is encapsulated in Command objects. A deployment is performed by one or more Command objects. Thus, the general pattern for using the deployer library is: