More corrections

03-vocabulary.md

@@ -116,6 +116,14 @@ These tools work in an **agentic loop**: they plan an action, use a tool to exec
 Examples include Cursor, Claude Code, and Cline.
 Unlike chat-based or autocomplete AI, agentic tools act like a team member with tools — they don't just suggest, they do.
 
+Good first issue
+: A GitHub label that identifies issues suitable for newcomers to a project or to open source in general.
+The concept emerged from the "first-timers-only" movement, popularized by developers like Scott Hanselman and Kent C. Dodds, to create approachable pathways into open source contribution.
+These issues are typically well-scoped bugs or minor enhancements with clear requirements, making them ideal starting points for new contributors.
+Projects use variations like "beginner-friendly," "easy-fix," or "low-hanging fruit."
+By marking issues this way, maintainers signal that their project welcomes beginners, helping grow their community while inviting people who might otherwise feel excluded from open source.
+Resources: [goodfirstissue.dev](https://goodfirstissue.dev/), [GitHub's guide](https://opensource.guide/building-community/), [How to Create Good Good-First-Issues](https://blogs.vmware.com/opensource/2019/10/16/open-source-good-first-issues/), [Finding Good First Issues](https://community.codenewbie.org/bdougie/finding-good-first-issues-33a6).
+
 LLM token
 : In the context of {term}`LLMs <LLM>`, a token is a unit of text (roughly 3-4 characters or ~0.75 words in English) that the model processes.
 API providers charge based on the number of tokens consumed—both input tokens (text sent to the model) and output tokens (text generated by the model).

04-materials/01-exploring-extensions.md

@@ -17,8 +17,8 @@
 
 It's not just an interface for working with Notebooks.
 The Notebook interface has been around since 2011, and in 2018,
-JupyterLab was introduced to provide a more comprehensive environment, like an operating
-system, for interactive computation.
+JupyterLab was introduced as an extensible IDE (Integrated Development Environment)
+for interactive computation.
 
 
 ## [The JupyterLab interface](https://jupyterlab.readthedocs.io/en/latest/user/interface.html)

04-materials/02-anatomy-of-extensions.md

@@ -45,7 +45,7 @@ This tutorial is inspired by many prior works.
     * Structure the activities around in person teaching and exercises
 :::
 
-
+(anatomy-setup)=
 ## 🛠️ Setup
 
 Before we get started, we need to set up:
@@ -197,7 +197,7 @@ Our extension will:
 
 🚀 Let's build it together from scratch.
 
-
+(anatomy-exercise-a)=
 ## 🏋️ Exercise A (15 minutes): Extension creation and development loop
 
 ### 🔧 Create a new extension from the [official template](https://github.com/jupyterlab/extension-template)
@@ -363,7 +363,7 @@ git push -u origin main
 
 ### 🔧 Do a complete development loop
 
-0. Close the JupyterLab server with `Ctrl+C`.
+0. Close the JupyterLab server. You can use the shutdown menu item in the JupyterLab itself (File → Shut Down), which is more reliable, or use `Ctrl+C` in the terminal where the server is running.
 
 1. Make any change to the codebase.
    For example, alter the text in a `console.log()` message.

04-materials/03-debugging.md

@@ -1,4 +1,4 @@
-# 🐞 4 - Debugging: What to do when things go wrong?
+# 🐞 3 - Debugging: What to do when things go wrong?
 
 :::{tip} Outcome
 By the end of this module, we'll have looked into JupyterLab extension development errors in both the terminal and browser console, and used the browser console functionalities to gather information that will help us resolve our errors.

04-materials/04-show-and-tell.md

@@ -1,4 +1,4 @@
-# 🪩 3 - Show & tell
+# 🪩 4 - Show & tell
 
 :::{hint} Learning objectives
 * Discover advanced applications for JupyterLab extensions

04-materials/06-working-on-your-own.md

@@ -29,7 +29,7 @@ All paths are valuable! Pick what excites you most.
 Before diving into your chosen path, make sure you have:
 
 - A clear goal (extension idea or GitHub issue to work on)
-- Development environment ready (if building new: follow [Setup](02-anatomy-of-extensions.md#️-setup) and [Exercise A](02-anatomy-of-extensions.md#️-exercise-a-15-minutes-extension-creation-and-development-loop))
+- Development environment ready (if building new: follow [Setup](02-anatomy-of-extensions.md#anatomy-setup) and [Exercise A](02-anatomy-of-extensions.md#anatomy-exercise-a))
 - Access to [JupyterLab API docs](https://jupyterlab.readthedocs.io/en/latest/api/) and [Extension Examples](https://github.com/jupyterlab/extension-examples)
 
 ## 🔨 Path 1: Build your own extension from scratch
@@ -40,10 +40,10 @@ Create something entirely new using the extension template, AI assistance, and t
 
 Follow these sections from chapter 2 to start a new extension from a template:
 
-1. [🛠️ Setup](02-anatomy-of-extensions.md#️-setup) - Set up your environment, Git, and GitHub repository
-2. [🏋️ Exercise A: Extension creation and development loop](02-anatomy-of-extensions.md#️-exercise-a-15-minutes-extension-creation-and-development-loop) - Create your extension from the template and test the development loop
+1. [🛠️ Setup](02-anatomy-of-extensions.md#anatomy-setup) - Set up your environment, Git, and GitHub repository
+2. [🏋️ Exercise A: Extension creation and development loop](02-anatomy-of-extensions.md#anatomy-exercise-a) - Create your extension from the template and test the development loop
 
-Once you have your extension set up and working, return here to choose an inspiration project below.
+Once you have your extension set up and working, proceed to work on your extension idea or return here to find inspiration below.
 
 ### 💫 Inspiration
 
@@ -81,13 +81,14 @@ To customize:
 Make the confetti more colorful and add a sound effect when it triggers.
 ```
 
-**Verified Setup**:
-- ✅ macOS 15.7, Claude Code (Claude Sonnet 4.5)
-- ✅ `conda` environment: Python 3.13, Node.js 22, JupyterLab
-- 📹 [Watch the demo](https://www.loom.com/share/2afabea0184045fa868271f9ab0ca083)
+**Setup**:
+- Tool: Claude Code
+- Model: Claude Sonnet 4.5
+
+<div style="position: relative; padding-bottom: 62.5%; height: 0;"><iframe src="https://www.loom.com/embed/2afabea0184045fa868271f9ab0ca083" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>
 
 :::{tip}
-This is a perfect first project - it's self-contained, purely visual, and you'll immediately see if it works. It teaches you about JupyterLab's status bar API without backend complexity.
+This is an ideal first project - it's self-contained, purely visual, and you'll immediately see if it works. It teaches you about JupyterLab's status bar API without backend complexity.
 :::
 
 #### 🎨 Custom theme extension
@@ -101,6 +102,17 @@ This is a perfect first project - it's self-contained, purely visual, and you'll
 Create a theme based on [your favorite movie/show/game/aesthetic]
 ```
 
+:::{tip} Better Results with Color Planning
+For better results, ask the LLM to plan the color palette first:
+```
+Create a theme based on [your theme]. First, suggest a UI color palette
+of 6 colors (background, foreground, accent, etc.) that match this theme,
+then implement the theme using those colors.
+```
+
+This explicit request for a color palette triggers more thoughtful planning before implementation!
+:::
+
 **Example**:
 ```
 Create a theme based on Netflix show KPop Demon Hunters
@@ -110,7 +122,7 @@ Create a theme based on Netflix show KPop Demon Hunters
 - A new theme appears in Settings → Theme menu
 - Theme includes custom colors matching your chosen aesthetic
 - JupyterLab interface reflects the theme's visual style
-- Theme can be toggled on/off
+- Theme can be toggled on/off in Settings → Theme menu
 
 **What to watch for**:
 
@@ -144,10 +156,16 @@ Use [specific colors] for accent elements.
 - Consider color palettes - extract 3-5 main colors from your chosen image (AI can help you with it!)
 - Free image sources: Unsplash, Pexels, Wallhaven
 
+**Setup**:
+- Tool: Cursor
+- Model: Claude Sonnet 4.5
+
+<div style="position: relative; padding-bottom: 62.5%; height: 0;"><iframe src="https://www.loom.com/embed/eff02e3cbc63430983f9448719bfa83c" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>
+
 :::{tip}
-This is a perfect creative project! You get immediate visual feedback, can personalize your JupyterLab environment, and learn how JupyterLab's theming system works. Plus, you'll have a custom theme you actually want to use daily.
+This is a solid creative project! You get immediate visual feedback, can personalize your JupyterLab environment, and learn how JupyterLab's theming system works. Plus, you'll have a custom theme you actually want to use daily.
 
-Themes are also great conversation starters - share your theme with other workshop participants!
+Themes are also good conversation starters - share your theme with other workshop participants!
 :::
 
 #### 📊 CPU monitor widget
@@ -193,14 +211,14 @@ Add a graph that shows CPU usage over the last 60 seconds,
 and highlight in red when usage is above 80%.
 ```
 
-**Verified setup**:
-- ✅ macOS 15.7, Cursor (Claude Sonnet 4.5 MAX)
-- ✅ `conda` environment: Python 3.13, Node.js 22, JupyterLab
-- ⚠️ Temperature data gracefully handled as N/A on macOS (expected)
-- 📹 [Watch the demo](https://www.loom.com/share/9f6d11d537a94a30af7559fd4d80eea2)
+**Setup**:
+- Tool: Cursor
+- Model: Claude Sonnet 4.5 MAX
+
+<div style="position: relative; padding-bottom: 62.5%; height: 0;"><iframe src="https://www.loom.com/embed/9f6d11d537a94a30af7559fd4d80eea2" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>
 
 :::{tip}
-This teaches you the full stack: backend API design, frontend-backend communication, error handling, and periodic updates. It's a perfect template for any monitoring or dashboard extension.
+This teaches you the full stack: backend API design, frontend-backend communication, error handling, and periodic updates. It's an excellent template for any monitoring or dashboard extension.
 :::
 
 ### 🌟 More extension ideas
@@ -214,9 +232,9 @@ Pick an idea that matches your comfort level and interests:
 4. **Pomodoro timer**: Status bar timer for focused work sessions with notifications
 
 #### 🚦 Intermediate (frontend + server)
-1. **File size analyzer**: Scan workspace directory and show largest files/folders
-2. **Git status widget**: Display current branch, uncommitted changes count
-3. **Environment inspector**: Show installed packages and Python version
+1. **File size analyzer**: Scan workspace directory and show largest files/folders. Bonus goal: Add a treemap visualization (like [WinDirStat](https://windirstat.net/)) to visually represent file sizes
+2. **Git status widget**: Display current branch, uncommitted changes count in the status bar
+3. **Environment inspector**: Show installed packages and Python version in the sidebar
 4. **Todo list with persistence**: Sidebar panel that saves tasks to disk
 
 #### 🎯 Advanced
@@ -248,7 +266,7 @@ Contributing to established extensions is a great way to learn real-world patter
 See our [Show & Tell session](04-show-and-tell.md) for a curated list of popular JupyterLab extensions and inspiration on projects to contribute to.
 
 #### 🐛 Beginner-friendly JupyterLab core
-Want to contribute to JupyterLab itself? Here are good first issues:
+Want to contribute to JupyterLab itself? Here are {term}`good first issues <good first issue>`:
 
 **JupyterLab Core:**
 - [Good First Issues](https://github.com/jupyterlab/jupyterlab/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)
@@ -259,11 +277,10 @@ Want to contribute to JupyterLab itself? Here are good first issues:
 
 ### ✅ Check the project needs
 **Check the project board or GitHub Issues** for:
+- {term}`"Good first issue" <good first issue>` labels
 - Feature requests that align with your interests
 - Bug reports you can reproduce
 - Documentation improvements
-
-**Browse recent issues** and look for:
 - Questions you can answer
 - Problems you've encountered yourself
 - Features you wish existed
@@ -292,6 +309,7 @@ Want to contribute to JupyterLab itself? Here are good first issues:
 
 3. **Make your changes**:
    - Start small - fix one thing at a time
+   - Make small commits for each "thing"
    - Follow the project's code style
    - Add or update tests if applicable
    - Update documentation
@@ -351,6 +369,7 @@ Before opening a PR, verify:
 - Commit messages are clear and descriptive
 - PR description explains what and why
 - You've read and followed CONTRIBUTING.md
+- Remove unused or unreachable code ("dead code") and unused artifacts (imports, variables, files, commented-out code)
 - Tests pass in CI/CD (after opening PR)
 
 ### 🔧 When contributing gets stuck