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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Orchestrate multi-agent coordination | 15–20% | - Design workflows for multiple agents - Define communication and handoff protocols - Monitor and troubleshoot multi-agent execution - Prevent conflicts and manage shared resources |
| Manage memory, state, and execution | 10–15% | - Handle execution flow, retries, and interruptions - Implement memory cleanup and expiration rules - Scope and persist agent state correctly - Choose memory types: short-term, long-term, external |
| Perform evaluation, error analysis, and tuning | 15–20% | - Define metrics and quality standards for outputs - Optimize prompts, tools, and behavior through iteration - Diagnose failures, hallucinations, and unexpected behavior - Test, validate, and compare agent results |
| Implement tool use and environment interaction | 20–25% | - Manage permissions and environment access - Connect agents to codebase, APIs, and external systems - Configure and extend GitHub Copilot agents - Implement tools, custom actions, and MCP servers |
| Implement guardrails and accountability | 10–15% | - Log actions, decisions, and changes for audit - Enforce least privilege and security boundaries - Ensure compliance, safety, and responsible use - Add validation, review, and approval gates |
| Prepare agent architecture and SDLC processes | 15–20% | - Design agent autonomy and decision boundaries - Plan agent deployment, monitoring, and maintenance - Integrate agents into software development lifecycle - Define agent purpose, scope, and success criteria |
Microsoft GitHub Agentic AI Developer Sample Questions:
1. 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) Ask mode
B) Plan mode
C) Agent mode
D) Edit mode
2. 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) The agent's GITHUB_TOKEN permissions, configured per workflow/repo policy
B) copilot-instructions.md
C) The /context command
D) .copilotignore
3. You want a reusable, shareable set of instructions that defines a specific persona/workflow (e.g.,
"security reviewer") that developers can invoke on demand in Copilot Chat, rather than instructions applied globally to every session. What should you create?
A) copilot-instructions.md
B) A prompt file (.prompt.md)
C) agents.md
D) .copilotignore
4. You have a GitHub Enterprise Cloud Organization that uses the GitHub Copilot coding agent.
Copilot creates a draft pull request for an assigned issue, and the pull request timeline shows Copilot started work.
After 70 minutes, the agent session log stops updating, and the pull request body status stops changing.
You need to restart the agent so that it continues the task from the issue context and produces new commits to the existing draft pull request.
What should you do?
A) Merge the draft pull request and mention @copilot on the merged pull request.
B) Select Approve and run workflows in the pull request merge box.
C) Unassign the issue from Copilot, and then reassign the issue to Copilot.
D) Wait for the agent to complete.
5. You want the Copilot coding agent to scan a large codebase and propose a full, human- reviewable step-by-step plan before writing any code. What should you do first?
A) Enable --allow-all
B) Switch to plan mode
C) Run /compact
D) Configure an MCP server
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: B |






