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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Orchestrate multi-agent coordination | 15–20% | - Multi-agent workflows
|
| Evaluation, error analysis, and tuning | 15–20% | - Tuning agent behavior
|
| Implement tool use and environment interaction | 20–25% | - Agent tool configuration
|
| Implement guardrails and accountability | 10–15% | - Guardrails and human-in-the-loop
|
| Manage memory, state, and execution | 10–15% | - Cross-tool continuity
|
| Prepare agent architecture and SDLC processes | 15–20% | - Planning vs execution boundaries
|
Microsoft GitHub Agentic AI Developer Sample Questions:
1. Case Study 2
Existing Environment
GitHub Environment
The GitHub environment contains the following:
- Three repositories named product-api, billing-service, and infra-terraform.
- Branch protection on the main branch in all repositories that requires at least one pull request review before merging
- GitHub Actions runners used across all workflows
- A GitHub team named SG_Dev that contains developers
- A GitHub team named SG_Review that contains senior engineers and a security team
- A .github/copilot-instructions.md file that includes general coding conventions for all features Agent environment The product-api repository uses a GitHub Copilot coding agent named agent1 that has the following configurations:
- No custom agent profile is defined.
- A Model Context Protocol (MCP) server named MCP1 is deployed to
https://mcp.litwareinc.internal and provides access to internal ticketing and deployment APIs.
MCP1 requires an API key for authentication.
A second Copilot coding agent named agent2 handles changes in infra-terraform and runs in parallel with agent1 when both agents have open assigned issues.
Copilot memory is NOT enabled for the organization.
Problem Statements
Litware identifies the following issues:
- During two recent sessions, agent1 accessed files in billing-service, which is outside the agent's intended scope.
- agent1 makes code changes immediately after receiving a task.
- A developer named Ben, who is on the SG_Dev team, reports that agent1 completed a session with a successful status and opened a pull request, but the pull request contains no file changes.
Other developers report this intermittently as well.
- Both agent1 and agent2 modified shared/config.yaml in a parallel test run, generating conflicting outputs.
agent1 consistently uses raw try-catch blocks for error handling, which violates the defined implementation guidelines of SG_Dev.
Requirements
Planned Changes
Litware plans to make the following changes:
- Ensure that agent1 can access all the tools in the environment.
- Provide product-api with specific instructions to agent1 without affecting Copilot Chat or Copilot code review.
- Configure MCP1 as a tool for agent1 by modifying the product-api repository MCP configuration.
- Ensure that Copilot retains details that it has learned and uses that knowledge for future work.
This must be applied to all licensed members of the organization.
Implementation guidelines
The development team at Litware identifies the following implementation guidelines:
- Agent workflows must be able to run in parallel.
- Application error handling must use the repository ErrorHandler class.
- agent1 and agent2 must run on isolated branches during parallel execution. File-level conflicts must be detected before merges, and both agents must be able to run concurrently.
Security requirements
Litware identifies the following security requirements:
- Only the members of SG_Review must be able to approve agent1 plan outputs.
- All API keys must be stored and accessed securely.
- The developers must NOT be able to self-approve.
Agent configuration
You need to resolve the issue of the agents generating conflicting output. The solution must meet the implementation guidelines.
What should you do?
A) Add shared/config.yaml to a CODEOWNERS file that requires SG_Review approval before any changes can be merged.
B) Configure each agent to work on a separate branch and add a required status check that detects file-level overlap before either pull request can be merged.
C) Configure tools: ['read', 'search'] in both agent profiles to prevent either agent from writing files.
D) Configure a concurrency group on both agent workflows so that only one workflow runs at a time.
2. You have a GitHub repository.
Developers use the GitHub Copilot CLI and repository-scoped hooks under .github/hooks/*.json.
You need to allow the Copilot CLI to automatically run low-risk Bash commands. The solution must prevent the autonomous execution of high-risk commands, such as sudo, rm -rf /, and curl ... | bash.
What should you do?
A) Configure a preToolUse hook that returns permissionDecision: "deny".
B) Configure a userPromptSubmitted hook that logs prompts and exits nonzero.
C) Add .github/hooks/logs/ to .gitignore.
D) Configure a sessionStart hook that prints a policy banner.
3. Drag and Drop Question
You have a GitHub repository that uses a custom GitHub Copilot coding agent defined in the rollout-bot.agent.md file.
You need to update a workflow so that agent-profile changes can be rolled back by reverting a single commit and rerunning the workflow. The workflow must check out the exact commit being deployed and apply the agent profile from the repository at that commit.
How should you complete the workflow? 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. Drag and Drop Question
You have a GitHub repository that uses the GitHub Copilot coding agent to resolve issues and create draft pull requests. The repository uses GitHub Actions for CI, and reviewers rely on pull request timelines and workflow artifacts to understand what the agent did.
During long-running agent tasks, the reviewers lose track of decisions and validation steps, which causes repeated questions and reworks when context drifts between iterations.
You need to persist task progress and decisions as durable artifacts and ensure that the reviewers can verify what the agent did during and after execution by using GitHub as the system of record.
What should you do for each requirement? To answer, drag the appropriate actions to the correct requirements. Each action 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.
5. Case Study 2
Existing Environment
GitHub Environment
The GitHub environment contains the following:
- Three repositories named product-api, billing-service, and infra-terraform.
- Branch protection on the main branch in all repositories that requires at least one pull request review before merging
- GitHub Actions runners used across all workflows
- A GitHub team named SG_Dev that contains developers
- A GitHub team named SG_Review that contains senior engineers and a security team
- A .github/copilot-instructions.md file that includes general coding conventions for all features Agent environment The product-api repository uses a GitHub Copilot coding agent named agent1 that has the following configurations:
- No custom agent profile is defined.
- A Model Context Protocol (MCP) server named MCP1 is deployed to
https://mcp.litwareinc.internal and provides access to internal ticketing and deployment APIs.
MCP1 requires an API key for authentication.
A second Copilot coding agent named agent2 handles changes in infra-terraform and runs in parallel with agent1 when both agents have open assigned issues.
Copilot memory is NOT enabled for the organization.
Problem Statements
Litware identifies the following issues:
- During two recent sessions, agent1 accessed files in billing-service, which is outside the agent's intended scope.
- agent1 makes code changes immediately after receiving a task.
- A developer named Ben, who is on the SG_Dev team, reports that agent1 completed a session with a successful status and opened a pull request, but the pull request contains no file changes.
Other developers report this intermittently as well.
- Both agent1 and agent2 modified shared/config.yaml in a parallel test run, generating conflicting outputs.
agent1 consistently uses raw try-catch blocks for error handling, which violates the defined implementation guidelines of SG_Dev.
Requirements
Planned Changes
Litware plans to make the following changes:
- Ensure that agent1 can access all the tools in the environment.
- Provide product-api with specific instructions to agent1 without affecting Copilot Chat or Copilot code review.
- Configure MCP1 as a tool for agent1 by modifying the product-api repository MCP configuration.
- Ensure that Copilot retains details that it has learned and uses that knowledge for future work.
This must be applied to all licensed members of the organization.
Implementation guidelines
The development team at Litware identifies the following implementation guidelines:
- Agent workflows must be able to run in parallel.
- Application error handling must use the repository ErrorHandler class.
- agent1 and agent2 must run on isolated branches during parallel execution. File-level conflicts must be detected before merges, and both agents must be able to run concurrently.
Security requirements
Litware identifies the following security requirements:
- Only the members of SG_Review must be able to approve agent1 plan outputs.
- All API keys must be stored and accessed securely.
- The developers must NOT be able to self-approve.
Agent configuration
You need to troubleshoot the issue reported by Ben.
What should you review?
A) the agent session log in the Agents panel
B) the GitHub Actions runner log for the session job
C) the GitHub Actions usage metrics of repo1
D) the GITHUB_TOKEN permissions block in the agent1 workflow
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: Only visible for members | Question # 4 Answer: Only visible for members | Question # 5 Answer: A |



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