small clarifying points

README.md

@@ -22,7 +22,7 @@ Refer to [`.env.example`](.env.example) for the format of their values as well a
 - `SYNAPSE_CONNECTION_URI`
 - `AWS_PROFILE` (or another source of AWS credentials)
 
-Once your environment is set, you can create a virtual environment, install the Python dependencies, and run the demonstration script (after downloading it) as follows. Note that you will need to update the `s3_prefix` parameter so that it points to an S3 bucket that is accessible to your Tower workspace.
+Once your environment variables are set, you can create a virtual environment, install the Python dependencies, and run the demonstration script (after downloading it) as follows. Note that you will need to update the `s3_prefix` parameter so that it points to an S3 bucket that is accessible to your Tower workspace.
 
 ### Manually creating a virtual environment
 ```bash
@@ -33,7 +33,8 @@ source venv/bin/activate
 # Install Python dependencies
 python3 -m pip install 'py-orca[all]' 'metaflow' 'pyyaml' 's3fs'
 
-# Run the script using an example dataset
+# Run the script using an example dataset.
+# Ensure that the S3 prefix contains a bucket your tower workspace has access to.
 python3 demo.py run --dataset_id 'syn51514585' --s3_prefix 's3://orca-service-test-project-tower-bucket/outputs'
 ```