diff --git a/src/ert/run_models/ensemble_experiment.py b/src/ert/run_models/ensemble_experiment.py
index 8162c243604..b2fc1243912 100644
--- a/src/ert/run_models/ensemble_experiment.py
+++ b/src/ert/run_models/ensemble_experiment.py
@@ -23,8 +23,8 @@
 class EnsembleExperiment(BaseRunModel):
     """
     This workflow will create a new experiment and a new ensemble from
-    the user configuration. It will never overwrite existing ensembles, and
-    will always sample parameters.
+    the user configuration.<br>It will never overwrite existing ensembles, and
+    will always sample parameters.<br>
     """
 
     def __init__(
diff --git a/src/ert/run_models/evaluate_ensemble.py b/src/ert/run_models/evaluate_ensemble.py
index de0079c57d9..cb190035c2e 100644
--- a/src/ert/run_models/evaluate_ensemble.py
+++ b/src/ert/run_models/evaluate_ensemble.py
@@ -25,12 +25,10 @@
 # pylint: disable=too-many-arguments
 class EvaluateEnsemble(BaseRunModel):
     """
-    This workflow will evaluate ensembles which have parameters, but no
-    simulation has been performed, so there are no responses. This can
-    be used in instances where the parameters are sampled manually, or
-    after performing a manual update step. This will always read parameter
-    and response configuration from the stored ensemble, and will not
-    reflect any changes to the user configuration on disk.
+    This workflow will evaluate ensembles which have parameters, but no simulation has been performed, so there are no responses.<br>
+    This can be used in instances where the parameters are sampled manually, or after performing a manual update step.<br>
+    The workflow will always read parameter and response configuration from the stored ensemble,<br>
+    and will not reflect any changes to the user configuration on disk.<br>
     """
 
     def __init__(
diff --git a/src/ert/run_models/single_test_run.py b/src/ert/run_models/single_test_run.py
index 0357d597c60..a6da0e57276 100644
--- a/src/ert/run_models/single_test_run.py
+++ b/src/ert/run_models/single_test_run.py
@@ -16,9 +16,9 @@
 class SingleTestRun(EnsembleExperiment):
     """
     Single test is equivalent to EnsembleExperiment, in that it
-    samples the prior and evaluates it. There are two key differences:
-    1) Single test run always runs locally using the local queue
-    2) Only a single realization is run
+    samples the prior and evaluates it.<br>There are two key differences:<br>
+    1) Single test run always runs locally using the <b>local queue</b><br>
+    2) Only a <b>single realization</b> (realization-0) is run<br>
     """
 
     def __init__(