Great idea! It seems that the first place tasks / command-line tasks are used is in "Ingesting raw data into the Butler repository."
In this case, it might be worth making a big deal of tasks/command-line tasks as part of this step.
The section title could become "Ingesting raw data into the Butler repository with a command-line task" — this would elevate the "task" keyword as folks are scanning the page.
Then how about starting the section with a brief discussion of tasks and their central importance with a link to the docs. So the section https://pipelines.lsst.io/v/d_2018_11_30/getting-started/data-setup.html#ingesting-raw-data-into-the-butler-repository would read like this:
The LSST Science Pipelines organizes data processing functionality into <it>tasks</it>. Tasks are highly configurable and therefore reusable with data from different cameras. Tasks are Python objects, so you can use them from your own scripts. Many tasks are also available as <it>command-line tasks</it> that you can run from the shell without having to write your own scripts. <link>Learn more about using command-line tasks</link>.
The next step in this tutorial is to populate the Butler repository you created in the previous step with data from <link>ci_hsc</link>. Run the <link>ingestImages.py</link> command-line task to do that:
ingestImages.py DATA $CI_HSC_DIR/raw/*.fits --mode=link
For most command-line tasks, the first argument is the Butler repository (the DATA directory). You can learn more about the command-line interface from <link https://pipelines.lsst.io/v/daily/modules/lsst.pipe.base/index.html#using-command-line-tasks>Using command-line tasks</link> documentation, or by running a task with the -h flag:
What do you think?