Microsoft GH-600 exam - in .pdf

GH-600 pdf
  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 11, 2026
  • Q & A: 85 Questions and Answers
  • PDF Price: $59.99
  • PDF Demo

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  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 11, 2026
  • Q & A: 85 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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Microsoft GH-600 exam - Testing Engine

GH-600 Testing Engine
  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 11, 2026
  • Q & A: 85 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Implement tool use and environment interaction20–25%- Configure and extend GitHub Copilot agents
- Connect agents to codebase, APIs, and external systems
- Implement tools, custom actions, and MCP servers
- Manage permissions and environment access
Orchestrate multi-agent coordination15–20%- Monitor and troubleshoot multi-agent execution
- Design workflows for multiple agents
- Define communication and handoff protocols
- Prevent conflicts and manage shared resources
Perform evaluation, error analysis, and tuning15–20%- Test, validate, and compare agent results
- Optimize prompts, tools, and behavior through iteration
- Diagnose failures, hallucinations, and unexpected behavior
- Define metrics and quality standards for outputs
Implement guardrails and accountability10–15%- Ensure compliance, safety, and responsible use
- Enforce least privilege and security boundaries
- Add validation, review, and approval gates
- Log actions, decisions, and changes for audit
Manage memory, state, and execution10–15%- Implement memory cleanup and expiration rules
- Choose memory types: short-term, long-term, external
- Handle execution flow, retries, and interruptions
- Scope and persist agent state correctly
Prepare agent architecture and SDLC processes15–20%- Integrate agents into software development lifecycle
- Plan agent deployment, monitoring, and maintenance
- Define agent purpose, scope, and success criteria
- Design agent autonomy and decision boundaries

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 branch protection rule and copilot-instructions.md
D) a ruleset and a .copilotignore file


2. 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.


3. You want to grant the Copilot coding agent access to only a narrowly scoped set of repository permissions (e.g., read code, write pull requests) rather than full admin access. What governs this scope?

A) copilot-instructions.md
B) .copilotignore
C) The /context command
D) The agent's GITHUB_TOKEN permissions, configured per workflow/repo policy


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. Drag and Drop Question
You have a GitHub repository that has a GitHub Actions workflow. The workflow runs an AI agent.
You need to ensure that the default GITHUB_TOKEN permissions are read-only, and write access is granted to only the job that performs repository write operations. The workflow must be able to create and approve pull requests only when explicitly enabled.
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.


Solutions:

Question # 1
Answer: B
Question # 2
Answer: Only visible for members
Question # 3
Answer: D
Question # 4
Answer: Only visible for members
Question # 5
Answer: Only visible for members

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