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#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.