Learn Eslint, Puppeteer and Reactfire

The pluggable linting utility for JavaScript and JSX.

eslint

One of the other tools I use is Emmet. It's used for writing HTML much more quickly by using shorthand. It can also be used for JSX. VSCode also supports ESLint which we will use and configure in our VSCode `settings.json`. I will also set up Prettier as my default formatter for TypeScript and TypeScript React files. 

Configure Emmet, ESlint, and Prettier Extensions

We can leverage GitHub Actions to automate the running of all of our accessibility auditing tools as part of a Continuous Integration (CI) workflow. 

Auditing tools will only catch a percentage of potential accessibility issues, it is no replacement for manual testing.  But being able to automate the auditing will add efficiencies to our testing and provide an early warning system that can be run much more frequently than it’s practical to perform manual testing.  Additionally, we can use our CI suite as a safety net to prevent code changes that break accessibility from being able to be merged.

## Resources
* https://app.egghead.io/lessons/react-set-up-eslint-to-audit-accessibility-issues-in-react
* https://docs.cypress.io/guides/continuous-integration/github-actions#Basic-Setup
* https://github.com/cypress-io/github-action

Automate Accessibility Audits with GitHub Actions

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

Nx already comes with a default TypeScript setup. Although you can opt-out of that and generate plain JS based components, especially in a large setup TypeScript can be beneficial in uncovering potential issues early. To add an extra level, Nx also comes with preconfigured eslint for all the apps and libraries. In this lesson we're going to explore the lint setup and how it can be used.

Linting a React app with Nx

JavaScript® (often shortened to JS) is a lightweight, interpreted, object-oriented language with first-class functions, most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic, and supports object-oriented, imperative, and functional programming styles.

javascript

In this lesson you will learn how to use the eslint yeoman generator to scaffold a new plugin to provide custom rules for your project. 
You will also be able to check the basic skeleton for an eslint ruleand a working example rule to apply a naming convention for async functions.

Scaffold an eslint Plugin with Yeoman

OpenGraph images are the images you see when you paste a link into a social platform and it "unfurls" into an image, title, and description. This happens on Twitter, Discord, Slack, and many other platforms. This collection goes over everything from designing OpenGraph images in Figma, to implementing them in CodeSandbox, to returning headless browser screenshots from Netlify Functions, and finally using Cloudinary as a write-through cache. 

You will come away from this collection with the ability to ship an API that you can use on any of your sites, and also on-demand, that can generate images for not only OpenGraph unfurls, but also for Instagram, GitHub, and more. Using headless browsers with playwright to generate our images means we get full access to all the responsive power of CSS and all the logical power of JS to handle layout, importing assets like pngs, choosing different fonts, and more.

The image below is generated via the project you'll build and deploy in this course

![An example opengraph image](https://relaxed-payne-d1bfbe.netlify.com/opengraph?title=Building%20an%20OpenGraph%20image%20generation%20API%20with%20Cloudinary%20Netlify%20Functions%20and%20React&tags=figma,netlify%20functions,playwright&author=chrisbiscardi)

Building an OpenGraph image generation API with Cloudinary, Netlify Functions, and React

Puppeteer is a Node library which provides a high-level API to control headless Chrome or Chromium over the DevTools Protocol. It can also be configured to use full (non-headless) Chrome or Chromium.

puppeteer

When taking screenshots, it's important that the browser is big enough to show all of the content in the DOM that we want to screenshot. We can do this by setting the viewport.

Setting the viewport on a Playwright headless browser

We have a number of options to use when testing for accessibility issues concerning alternative text for images.  The react-axe library and axe browser extension will both report when an image is missing alternative text.  The tota11y browser extension will annotate any images that are missing alternative text.  Running eslint with the eslint-plugin-jsx-a11y plugin installed will report on any `<img>` elements missing an `alt` attribute.  Finally, we can use a screen reader to actually hear what is read when an image has focus.

Test for Image Alternative Text Accessibility Issues

Images must have text alternatives that describe the information or function 
represented by them so they can be read and understood by those using screen readers.

## Alternative text for images
* All `<img>` elements should have an `alt` attribute provided
    * When not provided many screen readers will fallback to reading the file name instead
* The `alt` value should not include words like _“image”_, _“picture”_ or _“icon”_
    * Screen readers are already announcing that the element is an image
* Images that are decorative only and provide no information or function to the page should be hidden from Assistive Technologies by providing an empty `alt` attribute (`alt=””`)

## References
* https://www.w3.org/WAI/tutorials/images/
* https://www.w3.org/WAI/tutorials/images/decision-tree/
* https://www.w3.org/WAI/tutorials/images/tips/
* https://www.w3.org/WAI/tutorials/images/informative/
* https://www.w3.org/WAI/tutorials/images/functional/
* https://www.w3.org/WAI/tutorials/images/textual/

Define Images with Appropriate Text Alternatives

Our accessibility auditing toolkit makes it very easy for us to test for any form controls that are missing labels or are not correctly associated with their labels.  Running Eslint with the eslint-plugin-jsx-a11y installed will show us any form controls with missing or unassociated labels.  Running react-axe or using axe to audit a web page will similarly list any of these findings.  Finally using tota11y we can annotate any form controls on a page that are missing labels.  This is definitely some of the lower hanging fruit that we can easily find and fix when making our applications accessible!

Test for Form Control Label Accessibility Issues

Labeling inputs, elements, and widgets add context and clarity for assistive technology such as screen readers.  Elements of a `<form>` such as `<input>` or `<textarea>` or `<select>` should be labelled by using a `<label>` element.  Placeholder text can be used in addition to a label but should not be used in place of a label as not all assistive technologies respect placeholder text.

Ensure Form Controls have Accessible Labels

Our first layer of defense when building accessible React applications is to add some auditing tools to our development workflow. This should include adding static analysis checking for common accessibility standards and best practices. We can get this with the latest eslint plugin: "eslint-plugin-jsx-a11y". If you are already linting your projects adding this plugin should fit very smoothly into your workflow.

## Resources
1. [List of all the rules supported by eslint-plugin-jsx-a11y](https://github.com/evcohen/eslint-plugin-jsx-a11y#supported-rules)
2. [Comparison of the difference in rules between recommended and strict mode](https://github.com/evcohen/eslint-plugin-jsx-a11y#difference-between-recommended-and-strict-mode)
3. [Background on how the Accessibility API implemented by browsers interfaces with Assistive Technologies](https://github.com/evcohen/eslint-plugin-jsx-a11y#some-background-on-wai-aria-the-ax-tree-and-browsers)

Set up ESLint to Audit Accessibility Issues in React

JavaScript is great! JavaScript is also full of features and flexible options that can make it easy to introduce bugs. ESLint uses static analysis to check that your code adheres to a list of rules to help you avoid some specific runtime errors. ESLint is highly configurable, so in this lesson, we'll install ESLint and configure some baseline rules for our boilerplate.

Avoid Common JavaScript Errors with ESLint 

In this lesson we are going to use the firstPaintTime metric from chrome's load times, as well as the navigation start from the W3C window metrics, to calculate how long it takes a page to paint. We will set up a quick function and test it out on google.com

Calculate a Page's First Paint Time with Puppeteer

It can be helpful when automating tests, metrics, and integration tools to know not only how much JavaScript there is on a page but to calculate how much is not being used. We are able to calculate the percentage of JS used by getting metrics from the window object. 

Get the Percentage of Unused JS on a page with Puppeteer

In this lesson we are going to use Google's Puppeteer to gather metrics about a page's load time. We'll use a high level date subtraction method as well as gather data from the window performance timing. Then see how throttling the network to 3G affects the page's load time. 

Get a Page's Load Time with Puppeteer

In this lesson we are going to send commands to the chromium browser with Puppeteer. These commands will enable us to calculate both the total number of CSS stylesheets used on the page and the ruleUsage for each of those stylesheets. With these metrics we will be able to calculate the percentage of unused CSS on the page. 

Get the Percentage of Unused CSS on a Page with Google's Puppeteer

Nuclide is the IDE Facebook employees use to write React code. But setting it up to use Flow type checking and Eslint to lint files on the fly is tricky. This video shows you how. 

Setup Nuclide to use Flow and Eslint (Mac)

 We map over the initial set of results then use `Promise.all` to efficiently fetch the details of each pokemon rendered in the table. This allows us to add more columns to our pokemon table.

Fetch and display row details with Promise.all in Tanstack Table

map over the initial set of results then use `Promise.all` to efficiently fetch the details of each pokemon rendered in the tanstack table

Create a custom hook to fetch remote data by passing a promise to the React 19 `use` hook. Then render this data in Tanstack Table by memoizing the results and passing them to `useReactTable`.

Render remote data in a Tanstack Table with React 19's use hook and a promise

Create a custom hook using React 19’s use to fetch data with a promise. Render it in a Tanstack Table by memoizing and using useReactTable.

You know when you're deep in the code trenches and need someone to challenge your assumptions? That's exactly what this is about.

Instead of waiting for someone to poke holes in your master plan, you can paste that strategy straight into AI Studio and let it pressure test your ideas. We're talking about using this tool to validate everything from your feature proposals to your ambitious refactoring strategies.

The real magic happens when you hit that microphone button. Now you're in a real-time verbal sparring match. It's like rubber duck debugging but the duck actually pushes back and makes you defend every architectural decision you've made.

Here's the workflow:
1. Drop your master plan into the system instructions
2. Tell the AI to challenge every assumption
3. Hit that mic and defend your choices like you mean it
4. Watch your plan either emerge stronger or get rightfully dismantled

This approach is perfect when you're:
- Stuck in your own head with a complex problem
- Need to validate if your approach holds water
- Want to catch edge cases before they catch you
- Looking for opportunities you might have missed because you're too close to the code

It's like having a senior dev on call 24/7, ready to challenge your ideas and push you to think deeper about your solutions.

Now go forth and get your ideas challenged. Your projects will thank you for it.


An Uncomfortable and Challenging Conversation with AI Studio

In this lesson, you'll learn how to effectively brainstorm your project ideas before working with AI agents. We'll cover:

1. The importance of having a clear plan before starting work with AI agents
2. Using traditional brainstorming techniques to gather your thoughts
3. Leveraging video recording to capture your brainstorming session
4. How to review and analyze websites for inspiration
5. Documenting likes, dislikes, and potential features for your project
6. Using AI tools (like AI Studio) to organize and process your recorded brainstorming session

The lesson emphasizes a modern approach to brainstorming that combines traditional techniques with video recording, making it easier to later process your ideas through AI tools. This method helps ensure that no ideas are lost and that your thoughts can be effectively organized by AI for future reference.

How to Brainstorm Your Project Features to Prepare for AI Agents

Many people share .cursorrules files, but trying to craft your own from scratch is a huge pain. Instead, this lesson shows you how to grab ALL community-created .cursorrules files to build a custom rule set for your projects. We'll use Gitingest and Google AI Studio to gather these examples and generate an awesome starting point customized to your specific project.

Generate Custom .cursorrules for Your Project Based on Community Examples

Learn how to leverage the GitHub CLI to efficiently search through issues across multiple repositories and use that data with AI Studio for deeper insights.

You learn how to:

-  Search for specific issues across repositories using GitHub CLI
- Filtering issues based on criteria like comment count
- Extracting issue content and comments
- Using the collected data as context in AI Studio
- Creating practical applications like FAQs from issue discussions

The example demonstrates creating a Framer Motion FAQ by searching GitHub for issues with multiple comments, but the technique can be applied to any framework or library.

This workflow helps developers:
- Research common problems and solutions
- Understand recurring issues in specific technologies
- Generate useful documentation from real-world problems
- Make better use of existing GitHub discussions

This approach combines the power of GitHub's vast knowledge base with AI tools to create valuable insights for development work.

Search 100s of Issues with GitHub CLI as Context for AI Studio

I often find myself wondering how to use certain APIs in certain situations, and I have a couple of keywords that I try and search up on Google. 

What you can do in this situation is turn to GitHub and see how other people have actually used this code on public projects. The GitHub CLI enables us to run searches like this, and we can take the results and work on them programmatically.

Inside of Cursor with their Composer AI agent, we can search for the files we want, tell the agent to download them, and inspect them for better understanding of how those things work together.

Search All of GitHub's Code and Pass the Results to AI Agents in Cursor

Implement virtual scrolling to handle large datasets in an HTML table. Start with a basic table that renders 10,000 rows of data. The browser can struggle with this amount of DOM nodes to render at one time, especially on low end devices. 

We implement tanstack react virtual to render only the necessary amount of rows the user is viewing. The implementation includes proper column sizing, accessibility considerations, and convenient scroll controls, resulting in a smooth and performant table experience regardless of the dataset size.

Create a row virtualized HTML table with Tanstack Virtual

Learn how to implement virtual scrolling in React tables using TanStack Table and Tanstack Virtual with the useWindowVirtualizer React hook.

The most difficult tasks will require the strongest AI models. And those models simply aren't available as AI agents inside of your tooling. So the best workflows are to drag and drop the files you need to be changed and analyzed inside of a reasoning model such as OpenAI's O1 Pro, then letting it create a giant plan for your dumber AI agents to work on. The key here is that instead of just copying and pasting the entire plan into Cursors Composer or your AI agent, it's to create a file inside of your project and ask your agent to tackle the plan one step at a time. This allows you ample opportunity between each step to test and verify the micro steps along the way. Otherwise, as I've experienced many times, a session can go way off track and you burn a lot of time and burn a lot of AI requests Cursors Composer and it starts churning through a plan Cursors Composer and making lots of unwanted changes. Cursors Composer and it's to guide an AI agent to hold its hand along the way, especially through the most complex tasks. Cursors Composer and the most complex tasks Cursors Composer and the most complex tasks require a step-by-step plan.

Planning AI Agent Sessions with Reasoning Models

AI agents will inevitably make mistakes—it's just a matter of when. A key tool in your toolbox, once they do make mistakes after working on a problem for a while, is to use **git diff** to capture all of the changes they've made. 

Once you have those changes in a text file, you have a portable document that you can test against other AI models. This allows you to move the problem into smarter reasoning models with smaller context windows, helping you isolate and focus on the issue at hand.

**git diff** has been invaluable when working with AI agents because they'll often make many good changes but also slip in one tiny error. Finding that one small mistake is **git diff**’s superpower.

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