How To Automate Documentation Workflow For Developers — Smashing Magazine

How To Automate Documentation Workflow For Developers

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Quick summary ↬

In this article, you’ll learn how to save hours of tedious work of writing, updating, and correcting technical documentation. In this article, you will learn how to automate your documentation workflow with Vale and GitHub Actions.

To get the most out of this tutorial, you should be familiar with: Git, GitHub and Linux and the command line.

Why Should You Care About High-Quality Documentation?

Many teams struggle with writing documentation. When you go to check a framework, the documentation will often be out of date or unclear. This can lead to internal frustration when a team member tries to add a feature, but they don’t understand how the current feature works because of poor documentation. This can lead to unproductive hours on the job.

Poor documentation also compromises a good customer experience. According to Jeff Lawson, author of Ask Your Developer and founder of Twilio, if you are selling an API as a product, documentation is the ultimate advertisement for technical stakeholders. IBM did a study on the importance of documentation, and 90% of respondents admitted that they made their purchasing decisions based on the quality of a product’s documentation.

Writing good documentation is important for the developer and customer experiences.

If Documentation Is So Important, Then Why Do Engineering Teams Deprioritize It?

Writing documentation can break developers out of the “flow”. Documentation often lives outside of the main code base, and it is cumbersome to find and update. Putting it in an Excel spreadsheet or a proprietary CMS is not uncommon.

Automating documentation and improving documentation workflow fixes this.

Automating Documentation From a High Level

What does automating documentation mean? It means adopting common software development practices. When you automate documentation, you are:

The Style Guides

Before you use tools such as Vale and GitHub Actions to automate the style guide, let’s take a moment to define what exactly is a style guide.

You know that feeling when you are writing documentation and something seems a little off? Your explanations don’t fit the rest of the documentation, but you can’t quite describe why they’re wrong. The writing explains the concept, but it doesn’t seem to fit.

When you get this feeling, your voice and tone might be off. Refining the voice and tone is a way to make writing sound cohesive even if you are developing documentation that has been edited by the QA, engineering, and product teams. Below is an example style guide from the city bus application TAPP, taken from the book by Torrey Podmajersky.

TAPP is a transit application (for buses and trains). The header of the table announces TAPP’s values as a company, being efficient, trustworthy, and accessible. The left side of the table lists the different parts covered by the style guide: concepts, vocabulary, verbosity, grammar, and punctuation.

Together, these make a style guide. The header introduces the values, and the left side of the table shows the different components that you would find in any written material: vocabulary, grammar, and punctuation. The beauty of this style guide is that engineers and copywriters will clearly know what capitalization to use and which punctuation to use in order to promote Tapp’s brand identity.

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Technical Writing Style Guide

Not all style guides come in tables. Microsoft has a whole website that serves as a comprehensive guide, covering everything from acronyms to bias-free communication to chatbots. Microsoft of course isn’t the only company that has a style guide. Google has one, too.

The Trouble With Style Guides

Style guides are a great starting point for companies that are serious about documentation. They solve a lot of the confusion that developers might have about how exactly to write about a major feature that they are pushing out.

The problem with style guides is that they add friction to the writing process. Many writers, including me, don’t bother to stop writing and look at the style guide every time they have a question. Sometimes, a style guide is cumbersome and too difficult to reference — for instance, the Microsoft Style Guide is over a thousand pages long!

Linters and CI/CD for Documentation

If you are a programmer, then you are probably familiar with linters. Linters are an ideal way to enforce coding standards on your team. The same is true with documentation. When you create a linter, you are setting a benchmark of quality for your documentation. In this tutorial, we are going to use the Vale linter.

Using some sort of documentation automation alongside a linter is common. When we say automation in this context, we’re referring to the continuous integration and continuous deployment (CI/CD) workflow. CI automates the building and testing of documentation. CD automates the release of code.

You can use many different types of apps to implement a CI/CD workflow. In this tutorial, we are going to use GitHub Actions to run our documentation linter. GitHub Actions run CI directly in a GitHub repository, so there is no need to use a third-party application, such as CircleCI or Travis.

Finally, GitHub Actions are event-driven, which means they are triggered when something happens, such as when someone writes a pull request or an issue. In our example, a GitHub action will occur when someone pushes changes to their main branch.

GitHub Actions

First, create a GitHub repository. Then, locally, create a folder and cd into it.

Once you are in the folder, initialize the directory for Git.

Once you have initialized the repository, proceed to create a workflow directory to your folder.

Workflows are where we will store all of our GitHub actions. Once you’ve created a workflows folder, make a new workflow. We are going to name this workflow vale.yml.

Vale.yml is a YAML file. In this workflow file, we will include actions and jobs.

Now, open vale.yml in your favorite text editor.

Copy and paste the following into vale.yml, and let’s go over the context and syntax.

GitHub has a guide on all of the other workflow syntax and variables, in case you’re curious.

In this section, we have:

Next, we are going to customize our GitHub workflow to use Vale.

Set Up Vale in GitHub Actions File

Once we’ve copied the base workflow file, it is time to customize it, so that we can start using Vale actions. The first thing to do is change the name of the YAML file to Docs-Linting.

Next, we want to run the Vale test once someone has pushed their changes to the main branch on GitHub. We don’t want the test to run when someone creates a pull request, so we’ll delete that part of the YAML file.

The jobs section is the main part of the workflow file, and it is responsible for running the GitHub actions.

These actions are going to run on the latest version of Ubuntu. The Checkout action checks out the repository in order for the GitHub workflow to access it.

Now it is time to add a Vale action to our GitHub workflow.

We have named our action Vale. The uses variable shows which version of Vale we’re going to implement — ideally, we should use the most recent version. In the with variable, we set debug to true.

The styles section gives us the option to add a style guide to Vale. In this example, we are going to use write-good and Microsoft’s official style guide. Keep in mind that we can use other style guides as well.

The final part of this GitHub action is env. In order to run this GitHub action, we need to include a secret token.

This is what the result should look like:

Once you’ve finished making changes, save the file, commit to Git, and push your changes to GitHub.

To recap, in this section, we have:

In the next section, we are going to create a Vale configuration file.

Setting Up Vale Configuration File

Go to the root of your project’s directory, and then touch .vale.ini. Open .vale.ini in a text editor. Copy and paste the following into .vale.ini:

This set-up is the bare minimum. If you are interested in learning more about configuring Vale, head over to the documentation.

When you are finished making changes, save the file, and commit and push to GitHub.

In this part, we’ve learned the internals of a Vale configuration file. Now it’s time to create sample documentation.

Creating Documentation and Triggering the Vale GitHub Actions

Now it is time to see Vale and GitHub Actions in action! We are going to create a Markdown file and fill it with text. And we are going to get our text from DeLorean Ipsum.

Go to the root of your project, and then touch Once you’ve created the getting-started file, go to DeLorean Ipsum and create some dummy text for your documentation. Then, return to your text editor and paste the text in getting-started-md.

Save the file, commit it, and push it to GitHub.

Once you’ve pushed the changes, head over to GitHub where your repository is located. Go to the Actions tab.

You will see all of your workflows on the left side. We have only one, named Docs-Linting, the same name we put in the vale.yml file.

When we push the documentation to GitHub, we will trigger the action.

If the action has run without any problems, we will get a green checkmark.

Click on “Added docs” to get a full report.

You will see that we got 11 warnings. Let’s deal with the “weasel word” warning. Go back to the text editor, open, and delete the word “exactly”.

Save the changes, commit it to Git, and push the new version of the file to GitHub. It should trigger the GitHub action.

If we click on “Deleted the weasel word”, we will see that we have only 10 warnings now, and the “weasel word” warning is gone. Hooray!

We are finished, and we’ve covered a lot of ground. In this section, we have:

In a world that is increasingly going remote, prioritizing good documentation and good documentation workflow is important. You first have to define what “good” is by creating a style guide. Once you’ve figured out the rules of your documentation, then it’s time to automate.

Documentation should be treated like your code base: a living body of work that is constantly being iterated and becoming a bit better than the last time you updated it.

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(yk, al)

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