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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Orchestrate multi-agent coordination | 15-20% | - Coordinate multiple agents
|
| Topic 2: Implement guardrails and accountability | 10-15% | - Implement governance controls
|
| Topic 3: Prepare agent architecture and SDLC processes | 15-20% | - Integrate agents into the software development lifecycle
|
| Topic 4: Manage memory, state, and execution | 10-15% | - Control execution flow
|
| Topic 5: Implement tool use and environment interaction | 20-25% | - Select and configure agent tools
|
| Topic 6: Perform evaluation, error analysis, and tuning | 15-20% | - Evaluate agent performance
|
Microsoft GitHub Agentic AI Developer Sample Questions:
1. You have a GitHub Enterprise repository.
An agent opens pull requests to the main branch.
You need to ensure that changes to .github/workflows/* and /infra/* require approval from designated reviewers before merge.
What should you configure?
A) a ruleset and an agents.md file
B) a branch protection rule and a CODEOWNERS file
C) a ruleset and a .copilotignore file
D) a branch protection rule and copilot-instructions.md
2. An agent working through the Copilot coding agent in GitHub Actions needs additional build dependencies installed before it can run tests. Where should you define this setup?
A) copilot-instructions.md
B) .copilotignore
C) copilot-setup-steps.yml
D) agents.md
3. 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.
Hotspot Question
You need to implement agent2 to meet the technical requirements.
How should you complete the YAML configuration? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
4. Hotspot Question
You have a GitHub repository that uses the following GrtHub Copilot CLI command in a Bash script.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
5. You are running the GitHub Copilot CLI and want the agent to execute file edits and shell commands without prompting for confirmation on each individual action, during a trusted throwaway sandbox session. Which flag/command should you use?
A) --allow-all
B) /context
C) /compact
D) --agent=Task
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C | Question # 3 Answer: Only visible for members | Question # 4 Answer: Only visible for members | Question # 5 Answer: A |
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