Exercise: Getting Started with GitHub Copilot

@Sasmita07

Getting Started with GitHub Copilot

👋 Hey there @Sasmita07! Welcome to your Skills exercise!

Welcome to the exciting world of GitHub Copilot! 🚀 In this exercise, you'll unlock the potential of this AI-powered coding assistant to accelerate your development process. Let's dive in and have some fun exploring the future of coding together! 💻✨

✨ This is an interactive, hands-on GitHub Skills exercise!

As you complete each step, I’ll leave updates in the comments:

✅ Check your work and guide you forward
💡 Share helpful tips and resources
🚀 Celebrate your progress and completion

Let’s get started - good luck and have fun!

_{— Mona}

_{If you encounter any issues along the way please report them here.}

Step 1: Hello Copilot

Welcome to your "Getting Started with GitHub Copilot" exercise! 🤖

In this exercise, you will be using different GitHub Copilot features to work on a website that allows students of Mergington High School to sign up for extracurricular activities. 🎻 ⚽️ ♟️

📖 Theory: Getting to know GitHub Copilot

GitHub Copilot is an AI coding assistant that helps you write code faster and with less effort, allowing you to focus more energy on problem solving and collaboration.

GitHub Copilot has been proven to increase developer productivity and accelerate the pace of software development. For more information, see Research: quantifying GitHub Copilot’s impact on developer productivity and happiness in the GitHub blog.

As you work in your IDE, you'll most often interact with GitHub Copilot in the following ways:

Interaction Mode	📝 Description	🎯 Best For
⚡ Inline suggestions	AI-powered code suggestions that appear as you type, offering context-aware completions from single lines to entire functions.	Completion of the current line, sometimes a whole new block of code
💭 Inline Chat	Interactive chat scoped to your current file or selection. Ask questions about specific code blocks.	Code explanations, debugging specific functions, targeted improvements
💬 Ask Mode	Optimized for answering questions about your codebase, coding, and general technology concepts.	Understanding how code works, brainstorming ideas, asking questions
🤖 Agent Mode	Recommended default mode for most coding tasks: autonomous edits, tool use, and follow-through until the task is done.	Daily coding tasks, from scoped fixes to larger multi-file implementation work
🧭 Plan Agent	Optimized for drafting a plan and asking clarifying questions before any code changes are made.	When you want a reviewed plan first, then hand off to implementation

As you work, you'll find GitHub Copilot can help out in several places across the github.com website and in your favorite coding environments such as VS Code, Jet Brains, and Xcode!

For today's coding though, we will practice with VS Code in a pre-configured development environment known as a GitHub Codespace.

Tip

You can learn more about current and upcoming features in the GitHub Copilot Features documentation.

⌨️ Activity: Get a project intro from Copilot Chat

Let's start up our development environment, use copilot to learn a bit about the project, and then give it a test run.

Use the below button to open the Create Codespace page in a new tab. Use the default configuration.
Confirm the Repository field is your copy of the exercise, not the original, then click the green Create Codespace button.
- ✅ Your copy: /Sasmita07/github-copilot-learning
- ❌ Original: /skills/getting-started-with-github-copilot
Wait a moment for Visual Studio Code to load in your browser.
In the left sidebar, click the extensions tab and verify that the GitHub Copilot and Python extensions are installed and enabled.
At the top of VS Code, locate and click the Toggle Chat icon to open a Copilot Chat side panel.

🪧 Note: If this is your first time using GitHub Copilot, you will need to accept the usage terms to continue.
Make sure you are in Ask Mode for our first interaction
Enter the below prompt to ask Copilot to introduce you to the project.
```
Please briefly explain the structure of this project.
What should I do to run it?
```
🪧 Note: It is not necessary to follow Copilot's recommended instructions. We have already prepared the environment for you.
Now that we know a bit more about the project, let's actually try running it! In the left sidebar, select the Run and Debug tab and then press the Start Debugging icon.
We want to see our webpage running in a browser, so let's find the url and port. If it isn't visible, expand the lower panel and select the Ports tab.
In the list, find port 8000 and the related link. Hover over the link and select the Open in browser icon.

⌨️ Activity: Use Copilot to help remember a terminal command 🙋

Great work! Now that we are familiar with the app and we know it works, let's ask copilot for help starting a branch so we can do some customizing.

In VS Code's bottom panel, select the Terminal tab and on the right side click the plus + sign to create a new terminal window.

🪧 Note: This will avoid stopping the existing debug session that is hosting our web application service.
Within the new terminal window use the keyboard shortcut Ctrl + I (windows) or Cmd + I (mac) to bring up Copilot's Terminal Inline Chat.
Let's ask Copilot to help us remember a command we have forgotten: creating a branch and publishing it.
```
Hey copilot, how can I create and publish a new Git branch called "accelerate-with-copilot"?
```
💡 Tip: If Copilot doesn't give you quite what you want, you can always continue explaining what you need. Copilot will remember the conversation history for follow-up responses.
Press the Run button to let Copilot insert the terminal command for us. No need to copy and paste!
After a moment, look in the VS Code lower status bar, on the left, to see the active branch. It should now say accelerate-with-copilot. If so, you are all done with this step!
Now that your branch is pushed to GitHub, Mona should already be busy checking your work. Give her a moment and keep watch in the comments. You will see her respond with progress info and the next lesson.

Having trouble? 🤷

If you don't get feedback, here are some things to check:

Make sure your created the branch with the exact name accelerate-with-copilot. No prefixes or suffixes.
Make sure the branch was indeed published to your repository.

Step 1 - Passed ✅

Status	Description
✅ - Pass	Checked that branch name is accelerate-with-copilot

🎉🎉🎉 Nice work! Everything is perfect! 🎉🎉🎉
Preparing content for step 2! One moment... 🤓

Step 2: Getting work done with Copilot

In the previous step, GitHub Copilot was able to help us onboard to the project. That alone is a huge time saver, but now let's get some work done!

🐛 THERE IS A BUG ON THE WEBSITE 🐛

We’ve discovered that something’s off in the signup flow.
Students can currently register for the same activity more than once! Let’s see how far Copilot can take us in uncovering the cause and shaping a clean fix.

Before we dive in, a quick primer on how Copilot works. 🧑‍🚀

📖 Theory: How Copilot works

In short, you can think of Copilot like a very specialized coworker. To be effective with them, you need to provide them background (context) and clear direction (prompts). Additionally, different people are better at different things because of their unique experiences (models).

How do we provide context?: In our coding environment, Copilot will automatically consider nearby code and open tabs. If you are using chat, you can also explicitly refer to files.
What model should we pick?: For our exercise, it shouldn't matter too much. Experimenting with different models is part of the fun! That's another lesson! 🤖
How do I make prompts?: Being explicit and clear helps Copilot do the best job. But unlike some traditional systems, you can always clarify your direction with followup prompts.

Tip

There several other ways to supplement Copilot's knowledge and capabilities like chat participants, chat variables, slash commands, and MCP tools.

⌨️ Activity: Use Copilot to fix our registration bug 🐛

Let's ask Copilot to suggest where our bug might be coming from. Open the Copilot Chat panel in Ask mode and ask the following.
```
#codebase Students are able to register twice for an activity.
Where could this bug be coming from?
```
Now that we know the issue is in the src/app.py file and the signup_for_activity method, let's follow Copilot's recommendation and go fix it (semi-manually). We'll start with a comment and let Copilot finish the correction.
1. Open the src/app.py file.
  
  💡 Tip: If Copilot mentioned src/app.py in chat, you can click the file directly in the chat view to open it.
2. Near the bottom of the file, find the signup_for_activity function.
3. Find the comment line that describes adding a student. Above this is where it seems logical to do our registration check.
4. Enter the below comment and press enter to go to the next line. After a moment, temporary shadow text will appear with a suggestion from Copilot! Nice! 🎉
  
  Comment:
```
# Validate student is not already signed up
```
5. Press Tab to accept Copilot's suggestion and convert the shadow text to code.
Example Results

Copilot is growing every day and may not always produce the same results. If you are unhappy with the suggestions, here is an example of a valid suggestion result we produced during the making of this exercise. You can use it to continue forward.
```
@app.post("/activities/{activity_name}/signup")
def signup_for_activity(activity_name: str, email: str):
   """Sign up a student for an activity"""
   # Validate activity exists
   if activity_name not in activities:
      raise HTTPException(status_code=404, detail="Activity not found")

   # Get the activity
   activity = activities[activity_name]

   # Validate student is not already signed up
   if email in activity["participants"]:
     raise HTTPException(status_code=400, detail="Student is already signed up")

   # Add student
   activity["participants"].append(email)
   return {"message": f"Signed up {email} for {activity_name}"}
```

⌨️ Activity: Let Copilot generate sample data 📋

In new project developments, it's often helpful to have some realistic looking fake data for testing. Copilot is excellent at this task, so let's add some more sample activities and introduce another way to interact with Copilot using Inline Chat

Inline Chat and the Copilot Chat panel are similar, but differ in scope: Copilot Chat handles broader, multi-file or exploratory questions; Inline Chat is faster when you want targeted help on the exact line or block in front of you.

Near the top of the src/app.py file (about line 23), find the activities variable, where our example extracurricular activities are configured.
Highlight the entire activities dictionary by clicking and dragging your mouse from the top to the bottom of the dictionary. This will help provide context to Copilot for our next prompt.
Bring up Copilot inline chat by using the keyboard command Ctrl + I (windows) or Cmd + I (mac).

💡 Tip: Another way to bring up Copilot inline chat is: right click on any of the selected lines -> Open Inline Chat.

Enter the following prompt text and press enter or the Send button on the right.

Add 2 more sports related activities, 2 more artistic
activities, and 2 more intellectual activities.

After a moment, Copilot will directly start making changes to the code. The changes will be stylized differently to make any additions and removals easy to identify. Take a moment to inspect and verify the changes, and then press the Keep button.

Example Results

Copilot is growing every day and may not always produce the same results. If you are unhappy with the suggestions, here is an example result we produced during the making of this exercise. You can use it to continue forward, if having trouble.

# In-memory activity database
activities = {
   "Chess Club": {
      "description": "Learn strategies and compete in chess tournaments",
      "schedule": "Fridays, 3:30 PM - 5:00 PM",
      "max_participants": 12,
      "participants": ["michael@mergington.edu", "daniel@mergington.edu"]
   },
   "Programming Class": {
      "description": "Learn programming fundamentals and build software projects",
      "schedule": "Tuesdays and Thursdays, 3:30 PM - 4:30 PM",
      "max_participants": 20,
      "participants": ["emma@mergington.edu", "sophia@mergington.edu"]
   },
   "Gym Class": {
      "description": "Physical education and sports activities",
      "schedule": "Mondays, Wednesdays, Fridays, 2:00 PM - 3:00 PM",
      "max_participants": 30,
      "participants": ["john@mergington.edu", "olivia@mergington.edu"]
   },
   "Basketball Team": {
      "description": "Competitive basketball training and games",
      "schedule": "Tuesdays and Thursdays, 4:00 PM - 6:00 PM",
      "max_participants": 15,
      "participants": []
   },
   "Swimming Club": {
      "description": "Swimming training and water sports",
      "schedule": "Mondays and Wednesdays, 3:30 PM - 5:00 PM",
      "max_participants": 20,
      "participants": []
   },
   "Art Studio": {
      "description": "Express creativity through painting and drawing",
      "schedule": "Wednesdays, 3:30 PM - 5:00 PM",
      "max_participants": 15,
      "participants": []
   },
   "Drama Club": {
      "description": "Theater arts and performance training",
      "schedule": "Tuesdays, 4:00 PM - 6:00 PM",
      "max_participants": 25,
      "participants": []
   },
   "Debate Team": {
      "description": "Learn public speaking and argumentation skills",
      "schedule": "Thursdays, 3:30 PM - 5:00 PM",
      "max_participants": 16,
      "participants": []
   },
   "Science Club": {
      "description": "Hands-on experiments and scientific exploration",
      "schedule": "Fridays, 3:30 PM - 5:00 PM",
      "max_participants": 20,
      "participants": []
   }
}

You can now go to your website and verify that the new activities are visible.

⌨️ Activity: Use Copilot to describe our work 💬

Nice work fixing that bug and expanding the example activities! Now let's get our work committed and pushed to GitHub, again with the help of Copilot!

In the left sidebar, select the Source Control tab.

💡 Tip: Opening a file from the source control area will show the differences to the original rather than simply opening it.
Find the app.py file and press the + sign to collect your changes together in the staging area.
Above the list of staged changes, find the Message text box, but don't enter anything for now.
- Typically, you would write a short description of the changes here, but now we have Copilot to help out!
To the right of the Message text box, find and click the Generate Commit Message button (sparkles icon).
Press the Commit button and Sync Changes button to push your changes to GitHub.
Wait a moment for Mona to check your work, provide feedback, and share the next lesson.

Having trouble? 🤷

If you don't get feedback, here are some things to check:

Make sure your pushed the src/app.py file changes to the branch accelerate-with-copilot.

Step 2 - Passed ✅

Status	Description
✅ - Pass	New activities added to src/app.py. We found 9 activities (minimum 4 required)

🎉🎉🎉 Nice work! Everything is perfect! 🎉🎉🎉
Preparing content for step 3! One moment... 🤓

Step 3: Engage Hyperdrive - Copilot Agent Mode 🚀

📖 Theory: What is Copilot Agent Mode?

Copilot agent mode is the next evolution in AI-assisted coding. Acting as an autonomous peer programmer, it performs multi-step coding tasks at your command.

Copilot Agent Mode responds to compile and lint errors, monitors terminal and test output, and auto-corrects in a loop until the task is completed.

Agent Mode (at a glance)

Aspect	👩‍🚀 Agent Mode
Autonomy and planning	Breaks down high-level requests into multi-step work and iterates until the task is complete.
Context gathering	Uses your current context and can discover additional relevant files when needed.
Tool use	Selects and invokes tools automatically; you can also direct tools with mentions like `#codebase`.
Approval and safety gates	Sensitive actions can require approval before execution, helping you stay in control.

🧰 Agent Mode Tools

Agent mode uses tools to accomplish specialized tasks while processing a user request. Examples of such tasks are:

Finding relevant files to complete your prompt
Fetching contents of a webpage
Running tests or terminal commands

Tip

While VS Code provides many built‑in tools, you can also provide Agent Mode more domain‑specific powers through MCP tools.

Read more on MCP servers and GitHub MCP Server

Now, let's give Agent Mode a try! 👩‍🚀

⌨️ Activity: Use Copilot to add a new feature! 🚀

Our website lists activities, but it's keeping the guest list secret 🤫

Let's use Copilot to change the website to display signed up students under each activity!

At the bottom of Copilot Chat window, use the dropdown to switch to Agent mode.
Open the files related to our webpage then drag each editor window (or file) to the chat panel, informing Copilot to use them as context.
- src/static/app.js
- src/static/index.html
- src/static/styles.css
🪧 Note: Adding files as context is optional. If you skip this, Copilot Agent Mode can still use tools like #codebase to search for relevant files from your prompt. Adding specific files helps point Copilot in the right direction, which is especially useful in larger codebases.

💡 Tip: You can also use the Add Context... button to provide other sources of context items, like a GitHub issue or the results of a terminal window.
Ask Copilot to update our project to display the current participants of activities. Wait a moment for the edit suggestions to arrive and be applied.
```
Hey Copilot, can you please edit the activity cards to add a participants section.
It will show what participants that are already signed up for that activity as a bulleted list.
Remember to make it pretty!
```
After Copilot finishes work, you are in control of what changes get to stay.

Using the Keep buttons shown below, you can accept/discard all changes or review and decide change by change. This can be done either from the chat panel view or while inspecting each edited file.
Before we simply accept the changes, please check our website again and verify everything is updated as expected.

Here is an example of an updated activity card. You may need to restart the app or refresh the page.

🪧 Note: Your activity card may look different. Copilot won't always produce the same results.
Need help? 🤷

If the website is not loading, here are some things to check.
- Restart the VS Code Debugger to make sure the latest version of the website is served.
- If you forgot the url, or closed the window, please review step 1.
- Try hard refreshing the webpage or opening in a private window so it downloads a fresh copy.
Now that we have confirmed our changes are good, use the panel to cycle through each suggested edit and press Keep to apply the change.

💡 Tip: You can accept the changes directly, modify them, or provide additional instruction to refine them using the chat interface.

⌨️ Activity: Use Agent mode to add functional "unregister" buttons

Let's experiment with some more open-ended requests that will add more functionality to our web application.

If you don't get the desired results, you can try other models or provide follow-up feedback to refine the results.

Make sure your Copilot is still in Agent mode.
Click on the Tools icon and explore all Tools currently available to Copilot Agent Mode.
Time for our test! Let's ask Copilot to add functionality for removing participants.
```
#codebase Please add a delete icon next to each participant and hide the bullet points.
When clicked, it will unregister that participant from the activity.
```
The #codebase tool is used by Copilot to find relevant files, code chunks that are relevant to the task at hand.

🪧 Note: In this lab we explicitly include the #codebase tool to get the most repeatable results.
Feel free to try the prompt without #codebase and observe whether Agent Mode decides to gather broader project context on its own.
When Copilot is finished, inspect the code changes and the results on the website. If you like the results, press the Keep button. If not, try providing Copilot some feedback to refine the results.

🪧 Note: If you don't see updates on the website, you may need to restart the debugger
Ask Copilot to fix a registration bug.

💡 Tip: We recommend testing the registration flow yourself so you can clearly see the before/after changes behavior.
```
I've noticed there seems to be a bug.
When a participant is registered, the page must be refreshed to see the change on the activity.
```
When Copilot is finished, inspect the results and validate the registration flow on the website.

If you like the results, press the Keep button. If not, try providing Copilot some feedback.
Commit and push all your changes to the accelerate-with-copilot branch.
Wait for Mona to check your work and share the next step.

Step 3 - Passed ✅

Status	Description
✅ - Pass	Checked app.js for participant info
✅ - Pass	Checked styles.css for participant info

🎉🎉🎉 Nice work! Everything is perfect! 🎉🎉🎉
Preparing content for step 4! One moment... 🤓

Step 4: Plan your implementation with the Planning Agent 🧭

In the last step, Agent Mode helped us move fast and ship new functionality. 🚀

Now let's slow down for one round and work like architects: define a strong testing approach first, then hand it off for implementation. This gives us better clarity, fewer surprises, and cleaner results. 🧪

📖 Theory: What is Copilot Plan Agent?

Copilot Plan Agent helps you design a solution before any code is changed.

Instead of jumping straight into edits, it researches your request, asks clarifying questions, and drafts an implementation plan you can refine.

Plan Agent (at a glance)

Aspect	🧭 Plan Agent
Purpose	Creates a structured implementation plan before coding starts.
Context gathering	Uses read-only research to understand requirements and constraints.
Collaboration style	Asks clarifying questions, then updates the plan using your answers.
Iteration	Supports multiple refinement passes before implementation.
Safety	Does not edit files until you approve the plan and hand off to Agent Mode.
Handoff	Start implementation button hands off the approved plan to Agent Mode for coding.

Tip

You can start from a high-level request and then add constraints and details in follow-up prompts.

⌨️ Activity: Plan and implement backend tests

Your backend still has zero test coverage. Use Plan Agent to create a plan, answer questions, and then launch implementation.

Open the Copilot Chat panel and switch to Plan Agent.
Let's start with a broad prompt and Copilot will help us fill in the details:
```
I want to add backend FastAPI tests in a separate tests directory.
```
Wait for Copilot to generate its first plan. If it asks you any questions, answer them to the best of your ability.

🪧 Note: Don't worry about getting it perfect, you can always refine the plan later.

You can refine the plan and provide additional details in follow up prompts

Here are some examples:

Let's use the AAA (Arrange-Act-Assert) testing pattern to structure our tests

Make sure we use `pytest` and add it to `requirements.txt` file

Review the proposed plan and when you are happy with it, click Start implementation to hand off to Agent Mode.

Notice that clicking the button switched from Plan to Agent Mode. From this point on, Copilot can edit your codebase, just like before.
Watch Copilot implement the plan you just created. It may ask for permissions to run certain tools (e.g., run commands or create virtual environments). Approve these permissions so it can continue working.
Review the changes and make sure tests run successfully. If needed, continue guiding until implementation is complete.

🎯 Goal: Get all tests passing (green) before you move on. ✅

🪧 Note: Agent Mode may complete this in one pass, or it may need follow-up prompts from you.
Commit and push all your changes to the accelerate-with-copilot branch.
Wait for Mona to check your work and share the next step.

Having trouble? 🤷

If tests did not run, ask Copilot to run them for you.
Make sure pytest is added in requirements.txt and a tests/ directory exists.

Step 4 - Passed ✅

Status	Description
✅ - Pass	Checked for pytest in requirements.txt
✅ - Pass	Checked if tests are added in a separate directory

🎉🎉🎉 Nice work! Everything is perfect! 🎉🎉🎉
Preparing content for step 5! One moment... 🤓

Step 5: Using GitHub Copilot within a pull request

Congratulations! You are finished with coding for this exercise (and VS Code). Now it's time to merge our work. 🎉 To wrap up, let's learn about two limited-access Copilot features that can speed up our pull requests!

📖 Theory: GitHub Copilot for pull requests

Copilot pull request summaries

Typically, you would review your notes and commit messages then summarize them for your pull request description. This may take some time, especially if commit messages are inconsistent or code is not documented well. Fortunately, Copilot can consider all changes in the pull request and provide the important highlights, and with references too!

Copilot code review

More eyes on our work is always useful so let's ask Copilot to do a first pass before we do a normal peer review process. Copilot is great at catching common mistakes that are fixed by simple adjustments, but please remember to use it responsibly.

Note

These features are only available on paid plans of GitHub Copilot. [docs]

⌨️ Activity: Summarize and review a PR with Copilot

Both Copilot pull request summaries and Copilot code review have limited access, so this activity is mostly optional. If you don't have access, skip the optional steps of this activity.

In a web browser, open another tab and navigate to your exercise repository.
You might notice a notification banner suggesting to create a new pull request. Click that or use the Pull Requests tab at the top to create a new pull request. Please use the following details:
- base: main
- compare: accelerate-with-copilot
- title: Improve student activity registration system
(Optional) In the PR description toolbar click the Copilot icon and Summary action. After a moment, Copilot will add a description based on your changes. 📝
(Optional) In the right side information panel at the top, locate the Reviewers section and click the Request button next to a Copilot icon. Wait a moment for Copilot to add a review comment to your pull request!

💡 Tip: Notice a log entry that Copilot was requested for a review.
At the bottom, press the Merge pull request button. Nice work! You are all done! 🎉
Wait a moment for Mona to check your work, provide feedback, and post a final review of this exercise!

Please, follow the steps above.
I'll watch your progress in the background to provide feedback. 🧐

🎉🎉🎉 Nice work! Everything is perfect! 🎉🎉🎉
Now, let's do a quick review!

Review

Congratulations, you've completed this exercise and learned a lot about GitHub Copilot!

Here's a recap of the GitHub Copilot features you learned:

Ask Mode: Explored your codebase with Copilot
Inline suggestions: Completed code with Tab acceptance
Inline Chat: Generated code and data with Ctrl/Cmd + I
Agent Mode: Built features autonomously
Plan Agent: Drafted a plan, answered questions, and started implementation
GitHub integration: Generated commit messages, PR summaries, and code reviews

What's next?

Check out the other GitHub Skills exercises.
- Learn how to Integrate MCP with Copilot to give Copilot extra capabilities!
- Tailor Copilot to your project needs in Customize your GitHub Copilot Experience
- Tackle legacy COBOL code in Modernize Your Legacy Code with GitHub Copilot exercise
- Try GitHub Copilot Coding Agent in the Expand your team with Copilot exercise

@Sasmita07

Congratulations @Sasmita07! You finished the exercise! 🎉🎉🎉

We've updated the repository with a couple changes to highlight your success!

Return to the repository home page to see your progress!

Exercise: Getting Started with GitHub Copilot #1

Description

Getting Started with GitHub Copilot

Activity

github-actions commented on Apr 20, 2026

Step 1: Hello Copilot

📖 Theory: Getting to know GitHub Copilot

⌨️ Activity: Get a project intro from Copilot Chat

⌨️ Activity: Use Copilot to help remember a terminal command 🙋

github-actions commented on Apr 20, 2026

Step 1 - Passed ✅

github-actions commented on Apr 20, 2026

github-actions commented on Apr 20, 2026

Step 2: Getting work done with Copilot

📖 Theory: How Copilot works

⌨️ Activity: Use Copilot to fix our registration bug 🐛

⌨️ Activity: Let Copilot generate sample data 📋

⌨️ Activity: Use Copilot to describe our work 💬

github-actions commented on Apr 20, 2026

Step 2 - Passed ✅

github-actions commented on Apr 20, 2026

github-actions commented on Apr 20, 2026

Step 3: Engage Hyperdrive - Copilot Agent Mode 🚀

📖 Theory: What is Copilot Agent Mode?

Agent Mode (at a glance)

🧰 Agent Mode Tools

⌨️ Activity: Use Copilot to add a new feature! 🚀

⌨️ Activity: Use Agent mode to add functional "unregister" buttons

github-actions commented on Apr 20, 2026

Step 3 - Passed ✅

github-actions commented on Apr 20, 2026

github-actions commented on Apr 20, 2026

Step 4: Plan your implementation with the Planning Agent 🧭

📖 Theory: What is Copilot Plan Agent?

Plan Agent (at a glance)

⌨️ Activity: Plan and implement backend tests

github-actions commented on Apr 20, 2026

Step 4 - Passed ✅

github-actions commented on Apr 20, 2026

github-actions commented on Apr 20, 2026

Step 5: Using GitHub Copilot within a pull request

📖 Theory: GitHub Copilot for pull requests

Copilot pull request summaries

Copilot code review

⌨️ Activity: Summarize and review a PR with Copilot

github-actions commented on Apr 20, 2026

github-actions commented on Apr 20, 2026

github-actions commented on Apr 20, 2026

Review

What's next?

github-actions commented on Apr 20, 2026

Metadata

Metadata

Assignees

Labels

Projects

Milestone

Relationships

Development

Issue actions