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Microsoft GitHub Agentic AI Developer Sample Questions:

1. Case Study 1 - Contoso, Ltd
Overview
Contoso Ltd. is a software development company located in the United States.
Existing Environment
GitHub Environment
Contoso uses GitHub Enterprise and assigns GitHub Copilot Pro+ licenses to its developers. The developers use Microsoft Visual Studio Code as their IDE.
Contoso has a customer portal. The code for the portal is stored in a GitHub repository named repo1that contains the following:
- A custom agent named agent1 that includes instructions to review specs related to best practices
- A custom instruction file named validate-instructions.md that is used to validate tone of voice and applies to all .md and .txt files
- A custom instruction file named codereview.instructions.md that is used by the Copilot coding agent but is excluded for use by the Copilot code review repo1 has the following structure:
- The front-end is stored in the /frontend folder.
- The API logic is stored in the /api folder.
Contoso has a second repository named repo2 that contains a legacy .NET application named App1 built by using .NET 6. repo2 has a multi-agent workflow for modernization tasks.
Contoso enables the Model Context Protocol (MCP) registry and allows the Microsoft Learn MCP Server. Every developer must configure their own connection to the Learn MCP Server.
Problem Statements
The developers working in repo1 report that the Microsoft Learn documentation is NOT being retrieved when they attempt to validate a design by using agent1.
The testing team at Contoso identifies that the customer portal uses inconsistent UI styles, which leads to customer confusion and branding issues. The UI inconsistencies stem from variations in the folder structure.
Agent Logs
You have the following logs for the multi-agent workflow used in repo2.

Requirements
Planned Changes
Contoso plans to have all agents and developers in repo1use the Microsoft Learn MCP to ensure that reviews are validated by using the appropriate documentation. This must be implemented centrally.
Contoso plans to leverage AI-powered coding agents to implement new portal features and pages.
Technical Requirements
App1 must be upgraded to .NET 10. A previous upgrade attempt was started by using the Copilot modernization agent, but the attempt was never finalized.
You plan to retry the upgrade. You must first analyze App1 by using AI, and then generate a report that contains breaking changes and deprecated patterns before retrying the upgrade.
All AI-generated code for UI styling must adhere to a predefined folder structure.
The architects at Contoso need help building implementation plans for repo1. The company wants to implement a new agent named agent2 to analyze the code base and the code requirements, and then respond with a detailed plan. The agent must NOT be able to edit files or run local commands.
The developers must be able to delegate work to the Copilot coding agent by assigning issues to the agent.
Before App1 is upgraded, you need to verify each individual upgrade step and whether all tests have passed.
Which file should you use?

A) plan.md
B) assessment.md
C) tasks.md
D) agent.md

2. You have a GitHub repository that uses the GitHub Copilot coding agent.
Your company restricts GitHub Actions secrets.
Developers need the Copilot coding agent to call an internal dependency-scanning API during its run. The API requires an access token.
You need to ensure that the Copilot coding agent can use the token during execution without accessing the repository's Actions secrets and variables. The solution must prevent exposing the token in plaintext.
What should you do?

A) Add the token as an Actions repository secret.
B) Store the token in a repository custom instructions file.
C) Add the token as a secret in the Copilot environment.
D) Store the token in the agent configuration file.

3. You need finer control, selecting specific files and describing precise natural-language changes to apply, rather than letting the agent decide the full scope of changes. Which Copilot Chat mode should you use?

A) Agent mode
B) Plan mode
C) Edit mode
D) Ask mode

4. You need Copilot's coding agent to interact with an external ticketing system (e.g., Jira) so it can pull issue details as part of its workflow. What should you configure?

A) An MCP server
B) A branch protection ruleset
C) A CODEOWNERS entry
D) A .copilotignore rule

5. You want to prevent GitHub Copilot from ever suggesting completions or making edits inside a directory containing sensitive credentials templates. What should you configure?

A) A repository ruleset
B) A .copilotignore file
C) Branch protection rules
D) A CODEOWNERS file

Solutions: