Try and practice the latest Microsoft : GH-600 real questions & answers

Updated: Aug 02, 2026

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Microsoft GH-600 Exam Overview:

Certification Vendor:GitHub
Exam Name:GitHub Certified: Agentic AI Developer
Exam Number:GH-600
Exam Format:Proctored Exam, Scenario-based Questions, Interactive Exam Components
Related Certifications:GitHub Certified Foundations
GitHub Actions
GitHub Advanced Security
GitHub Copilot
Available Languages:English
Exam Duration:120 minutes
Certificate Validity Period:24 months
Sample Questions:Microsoft GH-600 Sample Questions
Exam Way:Pearson VUE testing center or online proctored exam.
Pre Condition:No formal prerequisites. Candidates should have experience with SDLC workflows, GitHub controls, GitHub Copilot, MCP servers, agent customization, code quality, security, and review practices.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/agentic-ai-developer/

Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement guardrails and accountability10-15%- Ensure accountability
  • 1. Establish human-in-the-loop processes
  • 2. Track actions and decisions
- Implement governance controls
  • 1. Configure approval workflows
  • 2. Apply security and compliance requirements
Topic 2: Manage memory, state, and execution10-15%- Control execution flow
  • 1. Monitor execution lifecycle
  • 2. Recover from interruptions and failures
- Manage context and memory
  • 1. Maintain agent state
  • 2. Handle long-running execution
Topic 3: Orchestrate multi-agent coordination15-20%- Ensure safe collaboration
  • 1. Prevent conflicts and unsafe actions
  • 2. Coordinate execution across agents
- Coordinate multiple agents
  • 1. Manage communication and task delegation
  • 2. Design multi-agent workflows
Topic 4: Implement tool use and environment interaction20-25%- Select and configure agent tools
  • 1. Identify required tools
  • 2. Configure tools and permissions
- Manage execution environments
  • 1. Control access to resources and services
  • 2. Configure environments for agents
Topic 5: Perform evaluation, error analysis, and tuning15-20%- Improve agent behavior
  • 1. Tune prompts, tools, and configurations
  • 2. Perform error analysis
- Evaluate agent performance
  • 1. Analyze scans, logs, and artifacts
  • 2. Measure outcomes and quality
Topic 6: Prepare agent architecture and SDLC processes15-20%- Integrate agents into the software development lifecycle
  • 1. Define inputs, outputs, and success criteria
  • 2. Identify steps for agents to perform
  • 3. Identify and mitigate agent anti-patterns
- Define boundaries between planning, reasoning, and action
  • 1. Validate and approve plans before execution
  • 2. Configure structured plans
  • 3. Separate planning from execution
- Configure observability and control
  • 1. Enable human intervention when required
  • 2. Generate inspectable artifacts
  • 3. Implement autonomy levels and guardrails

Microsoft GitHub Agentic AI Developer Sample Questions:

1. You have a GitHub repository.
You use the GitHub Copilot CLI to run an agentic workflow from the terminal.
During execution, the conversation history approaches the context limit. The agent cannot continue the current session unless the amount of retained context is reduced.
You need to continue the current session without losing all the prior progress.
Which Copilot CLI slash command should you run?

A) /compact
B) /context
C) /yolo
D) /clear


2. 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 branch protection rule and a CODEOWNERS file
B) a branch protection rule and copilot-instructions.md
C) a ruleset and an agents.md file
D) a ruleset and a .copilotignore file


3. Drag and Drop Question
You have a GitHub repository that uses GitHub Actions for CI on pull requests.
You have a GitHub Copilot coding agent that opens pull requests for backlog items, and your company requires automated checks for agent-generated changes.
You plan to standardize success criteria so that pull requests created by agents only succeed when unit tests pass and CodeQL analysis completes.
You need to configure a GitHub Actions workflow that runs on pull requests, executes unit tests, and performs CodeQL analysis.
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. You have a GitHub Copilot coding agent named CodeAgent. The .agent.md file of CodeAgent contains the following YAML frontmatter.
---
name: CodeAgent
description: Performs repository analysis and code review tasks.
tools: ['edit', 'execute', 'read', 'search']
---
You need to issue a GitHub Copilot CLI command that preserves execution velocity for read-only tasks by eliminating approval prompts for low-risk tools. The solution must ensure that high-risk tools that can make changes remain available but still require explicit user approval before running.
Which command should you run?

A) copilot agent run CodeAgent --deny-tool 'edit,execute'
B) copilot agent run CodeAgent --allow-tool 'read,search'
C) copilot agent run CodeAgent
D) copilot agent run CodeAgent --allow-all-tools
E) copilot agent run CodeAgent --allow-tool 'read,search' --deny-tool 'edit,execute'


5. 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 .copilotignore rule
C) A CODEOWNERS entry
D) A branch protection ruleset


Solutions:

Question # 1
Answer: A
Question # 2
Answer: A
Question # 3
Answer: Only visible for members
Question # 4
Answer: E
Question # 5
Answer: A

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