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Each exercise in `workshop-content/` contains a `## Scenario` section that describes the task in the context of Tailspin Toys. You will need to override this section for any exercise where the Tailspin-specific context does not make sense for your application.
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The core exercises in `workshop-content/`are generic templates. Each contains a `## Scenario` section and other sections describing tasks in application-neutral language. When your scenario needs scenario-specific content — your company name, tech-stack details, feature descriptions — create a steps file.
The override file should be a **complete exercise file** structured identically to the original in `workshop-content/`, with the `## Scenario` section rewritten for your application and any Tailspin-specific references replaced.
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It contains **only the `## ` sections that differ from the core**. When exercises are rendered for your scenario, each matching section in the steps file replaces its counterpart in the core exercise. Sections not present in the steps file are taken unchanged from the core.
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> [!TIP]
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> Start by copying the original exercise file, then search for "Tailspin" and replace every occurrence with your scenario's equivalent. Update code snippets and prompts to match your tech stack.
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> Only include the sections that genuinely differ. If only `## Scenario` needs to change, your steps file only needs that one section.
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### Minimal override example
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### Minimal steps file example
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If only the `## Scenario` section needs to change:
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If only the `## Scenario` section needs to change for exercise 1:
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```markdown
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<!-- scenarios/my-scenario/overrides/1-mcp.md -->
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# Exercise 1 - Setting up the backlog with Copilot agent mode and GitHub's MCP Server
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...same content as workshop-content/1-mcp.md, except:...
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## Scenario
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You are a developer for <CompanyName> — <company_description>. You've been
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assigned tasks to introduce new functionality. To file your backlog of issues
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you'll enlist the help of Copilot Chat in agent mode and the GitHub MCP server.
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```
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### Multi-section steps file example
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If exercises 3 needs a custom scenario description and application startup instructions:
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```markdown
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## Scenario
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As the list of <primary_entities> grows, <company_name> wants to allow users
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to filter by <filter_feature>. With the help of Copilot Agent Mode you'll add
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the new feature!
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## Running the application
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The <company_name> application is a <company_description>. It has two main
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components: a frontend written in <frontend_language> and a backend written
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in <backend_language>.
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### Starting the application
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...rest of file unchanged...
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...your tech-stack-specific startup steps here...
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```
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---
@@ -169,8 +183,8 @@ The script checks:
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- All required fields are present in `scenario.yml`.
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- Every exercise listed in `skip` exists in `workshop-content/`.
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- Every override file in `overrides/` corresponds to an exercise in `workshop-content/`.
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- No override exists for an exercise in the `skip` list (that would be a conflict).
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- Every steps file in `steps/` corresponds to an exercise in `workshop-content/`.
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- No steps file exists for an exercise in the `skip` list (that would be a conflict).
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Fix any issues reported before continuing.
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@@ -220,7 +234,7 @@ Use this checklist to track your progress:
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-[ ] Created scaffolding with `scripts/new-scenario.py`
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-[ ] Completed all fields in `scenario.yml`
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-[ ] Identified exercises to skip
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-[ ] Written overrides for exercises with Tailspin-specific content
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-[ ] Written steps files for exercises with scenario-specific content
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-[ ] Validated with `scripts/validate-scenario.py` (zero errors)
Before you get started on the lab, there's a few tasks you need to complete to get everything ready. You need to get a copy of the repository which includes the code, then spin up a [codespace][codespaces] to use to create your code.
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## Setting up the Lab Repository
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To create a copy of the repository for the code you'll create an instance from the [template][template-repository]. The new instance will contain all of the necessary files for the lab, and you'll use it as you work through the exercises.
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1. In a new browser window, navigate to the GitHub repository for this lab: `https://github.com/github-samples/agents-in-sdlc`.
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2. Create your own copy of the repository by selecting the **Use this template** button on the lab repository page. Then select **Create a new repository**.
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3. If you are completing the workshop as part of an event being led by GitHub or Microsoft, follow the instructions provided by the mentors. Otherwise, you can create the new repository in an organization where you have access to Copilot coding agent and can assign issues to Copilot.
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4. Make a note of the repository path you created (**organization-or-user-name/repository-name**), as you will be referring to this later in the lab.
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## Creating a codespace
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Next up, you'll be using a codespace to complete the lab exercises. [GitHub Codespaces][codespaces] are a cloud-based development environment that allows you to write, run, and debug code directly in your browser. It provides a fully-featured IDE with support for multiple programming languages, extensions, and tools.
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1. Navigate to your newly created repository.
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2. Select the green **Code** button.
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3. Select the **Codespaces** tab and select the **+** button to create a new Codespace.
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The creation of the codespace will take several minutes, although it's still far quicker than having to manually install all the services! That said, you can use this time to explore other features of GitHub Copilot, which we'll turn your attention to next!
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> [!IMPORTANT]
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> You'll return to the codespace in a future exercise. For the time being, leave it open in a tab in your browser.
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## Summary
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Congratulations, you have created a copy of the lab repository! You also began the creation process of your codespace, which you'll use when you begin writing code.
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## Next step
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Let's explore how you can use Model Context Protocol (MCP) to interact with external services! You can do this by [setting up the backlog with Copilot agent mode and GitHub's MCP Server](./1-mcp.md).
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