GH-600 Certification Exam Guide + Practice Questions Updated 2026

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Comprehensive GH-600 certification exam guide covering exam overview, skills measured, preparation tips, and practice questions with detailed explanations.

GH-600 Exam Guide

This GH-600 exam focuses on practical knowledge and exam application scenarios related to the subject area. It evaluates your ability to understand core concepts, apply best practices, and make informed decisions in realistic situations rather than relying solely on memorization.

This page provides a structured exam guide, including exam focus areas, skills measured, preparation recommendations, and practice questions with explanations to support effective learning.

 

Exam Overview

The GH-600 exam typically emphasizes how concepts are used in professional environments, testing both theoretical understanding and practical problem-solving skills.

 

Skills Measured

  • Understanding of core concepts and terminology
  • Ability to apply knowledge to practical scenarios
  • Analysis and evaluation of solution options
  • Identification of best practices and common use cases

 

Preparation Tips

Successful candidates combine conceptual understanding with hands-on practice. Reviewing measured skills and working through scenario-based questions is strongly recommended.

 

Practice Questions for GH-600 Exam

The following practice questions are designed to reinforce key GH-600 exam concepts and reflect common scenario-based decision points tested in the certification.

Question#1

DRAG DROP
You have a GitHub repository that has a GitHub Actions workflow. The workflow runs an AI agent that deploys a containerized service.
You need to update the workflow so that only one production deployment can run at a time, and any currently running production deployments are cancelled when a new run starts.
How should you complete the workflow? To answer, drag the appropriate values to the correct targets.


A. 

Explanation:
Top-level property concurrency
Concurrency-group property group
Cancellation property cancel-in-progress
Result:
concurrency:
group: production cancel-in-progress: true
The concurrency block defines a shared execution group. Assigning group: production places all production deployment runs into the same group, preventing simultaneous deployments to that target.
Setting cancel-in-progress: true changes the default behavior by cancelling an active deployment when a newer workflow run enters the group. This ensures that only the latest production deployment continues rather than allowing an outdated deployment to finish after a newer version has been requested.
The concurrency block is normally placed at the workflow level when the policy applies to the full deployment workflow. It can also be scoped to a job when only a specific deployment job needs coordination. The environment name identifies the production target, but environment configuration alone does not impose the required single-active-run and cancellation behavior.
A production concurrency group should be reserved for operations that genuinely target the same deployment resource. Reusing it for unrelated jobs would unintentionally serialize unrelated work.
Study-guide topics: deployment coordination, concurrency groups, cancellation policy, and safe production execution.
Reference: GitHub Actions―Control concurrency.

Question#2

You are about to start a complex refactoring task in the GitHub Copilot CLI.
Before Copilot makes any changes, you need to review and agree on the approach.
What should you do first?

A. Start the Copilot CLI and specify the --agent=Task parameter.
B. Start the Copilot CLI and specify the --allow-all parameter.
C. From the Copilot CLI, switch to plan mode.
D. From the Copilot CLI, run the /compact command.

Question#3

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 userPromptSubmitted hook that logs prompts and exits nonzero.
B. Add .github/hooks/logs / to .gitignore.
C. Configure a sessionStart hook that prints a policy banner.
D. Configure a preToolUse hook that returns permissionDecision: "deny".

Question#4

In Microsoft Visual Studio Code, you are using GitHub Copilot Chat to generate documentation for a new feature.
Earlier in the day, you used Copilot Chat extensively for an unrelated refactoring task.
You discover that the Copilot responses for the new documentation task are influenced by the earlier conversation.
You need Copilot to focus only on the current task and avoid using prior conversational context. The solution must NOT affect other conversations.
What should you do?

A. Clear the chat history of the current conversation.
B. Change from sidebar chat to inline chat.
C. Use @file to restrict the Copilot context to the currently open file.
D. Start a new Copilot Chat conversation.
E. Modify the Chat > Agent: Max Requests setting.

Explanation:
Starting a new Copilot Chat conversation establishes a separate conversational context for the documentation task. The unrelated refactoring exchanges remain in their original conversation instead of continuing to influence the new thread. This directly addresses the requirement to separate tasks while preserving other conversations.
Conversation history contributes information beyond the latest prompt. Earlier instructions, assumptions, terminology, and design decisions can continue to affect subsequent responses within the same session. A fresh conversation provides a clear task boundary, allowing the developer to supply the feature requirements and relevant documentation context explicitly.
Changing from sidebar chat to inline chat changes the interaction surface; it does not provide the same explicit separation of conversational history. Referencing a file supplies relevant context but does not reliably remove earlier instructions. The maximum requests setting governs agent execution limits rather than conversation isolation. Clearing history is also unnecessary when the previous work can remain available in its own session.
A new conversation can still receive applicable repository instructions and deliberately supplied context; it is the previous conversation that is separated.
Study-guide topics: conversational state, context isolation, and task boundaries.
Reference: VS Code―Manage agent sessions.

Question#5

While using agent mode in VS Code, you want Copilot to run a specific test suite as a validation step after making changes, without manually invoking the terminal each time.
What feature enables this?

A. MCP server integration
B. Tool/terminal invocation permissions in agent mode
C. .copilotignore
D. CODEOWNERS

Explanation:
In VS Code agent mode, GitHub Copilot can use built-in tools to perform actions required to complete and validate a development task. One of these capabilities is the terminal tool
, which allows the agent to execute commands such as builds, linters, package-management operations, and test suites directly through VS Code's integrated terminal. The user can explicitly instruct the agent to make changes and then run a designated test command to verify the result.
The relevant control is the agent'stool and terminal invocation permissions. Depending on configured approval policies, Copilot can request authorization for a terminal command or execute approved commands as part of its iterative workflow. This allows validation to become part of the agent's task rather than requiring the developer to manually open the terminal after every modification. GitHub documentation specifically describes agent mode as capable of making edits, issuing terminal commands, observing results, and iterating when necessary.
Option A is unnecessary because running a local test suite does not require an MCP server. .copilotignore concerns context/access exclusions, while CODEOWNERS defines repository ownership and review responsibilities rather than agent execution capabilities. Study Guide Reference Topics: Implement Tool Use and Environment Interaction; terminal tools; agent permissions; automated validation; iterative tool execution.

Disclaimer

This page is for educational and exam preparation reference only. It is not affiliated with Microsoft, GitHub Certified: Agentic AI Developer, or the official exam provider. Candidates should refer to official documentation and training for authoritative information.

Exam Code: GH-600Q & A:  109  Q&As Updated:  2026-10-15

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