diff --git a/src/nupic/frameworks/opf/exp_description_api.py b/src/nupic/frameworks/opf/exp_description_api.py
index e8195f5234..2474ebfa69 100644
--- a/src/nupic/frameworks/opf/exp_description_api.py
+++ b/src/nupic/frameworks/opf/exp_description_api.py
@@ -122,8 +122,44 @@ def convertNupicEnvToOPF(self):
 
 
 class ExperimentDescriptionAPI(DescriptionIface):
-  """
-  TODO: Document this.
+  """Interface for specifying OPF experiments.
+
+  This class is used to specify the model and control parameters for an OPF
+  experiment. The model config includes the necessary information for
+  constructing an OPF model and the control includes information about the
+  environment, where to get the data from, etc.
+
+  The :mod:`~nupic.frameworks.opf.experiment_runner` takes an instance of
+  this class as the description of the experiment to run. Similarly,
+  `scripts/run_opf_experiment.py` looks for an instance of this class in a
+  variable called "descriptionInterface" in the experiment files that are
+  passed to it.
+
+  :param modelConfig: (dict) a specification of the model to use, including
+      the following keys:
+
+          - **model**: the name of the OPF model to create
+          - **version**: the config format version to use
+          - **modelParams**: parameters to pass to the OPF model
+
+      There may be other required fields such as predictionSteps,
+      predictedField, and numRecords
+
+  :param control: (dict): a specification of the experimental setup,
+      including the following keys:
+
+          - **environment**: the environment that the model will be run in
+          - **dataset**: input specification as defined in
+              `src/nupic/frameworks/opf/jsonschema/stream_def.json`
+          - **iterationCount**: maximum number of iterations, or -1 to iterate
+              until the data source is exhausted
+          - **inferenceArgs**: a dict containing all the supplementary parameters
+              for inference, including "predictedField" and "predictionSteps"
+          - **metrics**: a list of MetricSpec instances that specify the metrics to
+              compute during this experiment
+          - **loggedMetrics**: a sequence of regular expression strings that
+              specify which metrics should be logged at each iteration of the
+              experiment
   """
 
   def __init__(self, modelConfig, control):