diff --git a/docs/examples.rst b/docs/examples.rst
index 15ce2a2..6ba3b26 100644
--- a/docs/examples.rst
+++ b/docs/examples.rst
@@ -179,6 +179,8 @@ here's an example of how you can have Django Q take care of your indexes in real
 Now every time a Document is saved, your indexes will be updated without causing a delay in your save action.
 You could expand this to dealing with deletes, by adding a ``post_delete`` signal and calling ``index.remove_object`` in the async function.
 
+.. _shell:
+
 Shell
 =====
 You can execute or schedule shell commands using Pythons :mod:`subprocess` module:
@@ -267,7 +269,7 @@ Adapted from `Sebastian Raschka's blog <http://sebastianraschka.com/Articles/201
                 k_n += 1
         return h, (k_n / len(x_samples)) / (h ** point_x.shape[1])
 
-    # create 100 calculations and send them to the cluster
+    # create 100 calculations and return the collated result
     def parzen_async():
         # clear the previous results
         delete_group('parzen', cached=True)
@@ -292,8 +294,7 @@ Alternatively the ``parzen_async()`` function can also be written with :func:`as
 
 .. code-block:: python
 
-    # create 100 calculations and send them to the cluster
-    # with async_iter
+    # create 100 calculations and return the collated result
     def parzen_async():
         mu_vec = numpy.array([0, 0])
         cov_mat = numpy.array([[1, 0], [0, 1]])
diff --git a/docs/schedules.rst b/docs/schedules.rst
index 2ba210f..f5a6713 100644
--- a/docs/schedules.rst
+++ b/docs/schedules.rst
@@ -85,6 +85,7 @@ Or you can make a wrapper function which you can then schedule in Django Q:
     schedule('tasks.clear_sessions_command', schedule_type='H')
 
 
+Check out the :ref:`shell` examples if you want to schedule regular shell commands
 
 Reference
 ---------
diff --git a/docs/tasks.rst b/docs/tasks.rst
index f1a0fb1..e9b1df6 100644
--- a/docs/tasks.rst
+++ b/docs/tasks.rst
@@ -187,7 +187,7 @@ By using a cache backend like Redis or Memcached you can speed up access to your
 
 When you set ``cached=True``, results will be saved permanently in the cache and you will have to rely on your backend's cleanup strategies (like LRU) to
 manage stale results.
-You can also opt to set a manual timeout on the results, by setting ``cached=60``. Meaning the result will be evicted from the cache after 60 seconds.
+You can also opt to set a manual timeout on the results, by setting e.g. ``cached=60``. Meaning the result will be evicted from the cache after 60 seconds.
 This works both globally or on individual async executions.::
 
     # simple cached example
@@ -199,8 +199,8 @@ This works both globally or on individual async executions.::
     # wait max 50ms for the result to appear in the cache
     result(id, wait=50, cached=True)
 
-    # o fetch the task object
-    task = fetch(id, cache=True)
+    # or fetch the task object
+    task = fetch(id, cached=True)
 
     # and then save it to the database
     task.save()