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Microsoft GH-600 valid exam - in .pdf Free Demo

  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Last Updated: Aug 19, 2026
  • Q & A: 85 Questions and Answers
  • Convenient, easy to study. Printable Microsoft GH-600 PDF Format. It is an electronic file format regardless of the operating system platform. 100% Money Back Guarantee.
  • PDF Price: $59.98    

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  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Last Updated: Aug 19, 2026
  • Q & A: 85 Questions and Answers
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Microsoft GH-600 Exam Syllabus Topics:

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

Microsoft GitHub Agentic AI Developer Sample Questions:

1. Your team wants Copilot's suggestions to reflect knowledge of internal library APIs that are not publicly documented and not present in the codebase being edited. What is the most appropriate solution?

A) Use .copilotignore to hide public APIs
B) Add the internal docs as copilot-instructions.md
C) Enable plan mode
D) Connect an MCP server that exposes the internal documentation


2. 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) Switch to plan mode
B) Enable --allow-all
C) Configure an MCP server
D) Run /compact


3. You have a GitHub Enterprise organization that has Copilot memory enabled.
You create a new repository.
What are two ways that memories will be deleted from the repository? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A) when pull requests are merged
B) when the code that created the memory is deleted
C) automatically after 28 days
D) manually by repository members
E) when the repository is archived


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


5. Case Study 2
Existing Environment
GitHub Environment
The GitHub environment contains the following:
- Three repositories named product-api, billing-service, and infra-terraform.
- Branch protection on the main branch in all repositories that requires at least one pull request review before merging
- GitHub Actions runners used across all workflows
- A GitHub team named SG_Dev that contains developers
- A GitHub team named SG_Review that contains senior engineers and a security team
- A .github/copilot-instructions.md file that includes general coding conventions for all features Agent environment The product-api repository uses a GitHub Copilot coding agent named agent1 that has the following configurations:
- No custom agent profile is defined.
- A Model Context Protocol (MCP) server named MCP1 is deployed to
https://mcp.litwareinc.internal and provides access to internal ticketing and deployment APIs.
MCP1 requires an API key for authentication.
A second Copilot coding agent named agent2 handles changes in infra-terraform and runs in parallel with agent1 when both agents have open assigned issues.
Copilot memory is NOT enabled for the organization.
Problem Statements
Litware identifies the following issues:
- During two recent sessions, agent1 accessed files in billing-service, which is outside the agent's intended scope.
- agent1 makes code changes immediately after receiving a task.
- A developer named Ben, who is on the SG_Dev team, reports that agent1 completed a session with a successful status and opened a pull request, but the pull request contains no file changes.
Other developers report this intermittently as well.
- Both agent1 and agent2 modified shared/config.yaml in a parallel test run, generating conflicting outputs.
agent1 consistently uses raw try-catch blocks for error handling, which violates the defined implementation guidelines of SG_Dev.
Requirements
Planned Changes
Litware plans to make the following changes:
- Ensure that agent1 can access all the tools in the environment.
- Provide product-api with specific instructions to agent1 without affecting Copilot Chat or Copilot code review.
- Configure MCP1 as a tool for agent1 by modifying the product-api repository MCP configuration.
- Ensure that Copilot retains details that it has learned and uses that knowledge for future work.
This must be applied to all licensed members of the organization.
Implementation guidelines
The development team at Litware identifies the following implementation guidelines:
- Agent workflows must be able to run in parallel.
- Application error handling must use the repository ErrorHandler class.
- agent1 and agent2 must run on isolated branches during parallel execution. File-level conflicts must be detected before merges, and both agents must be able to run concurrently.
Security requirements
Litware identifies the following security requirements:
- Only the members of SG_Review must be able to approve agent1 plan outputs.
- All API keys must be stored and accessed securely.
- The developers must NOT be able to self-approve.
Agent configuration

You need to troubleshoot the issue reported by Ben.
What should you review?

A) the agent session log in the Agents panel
B) the GitHub Actions usage metrics of repo1
C) the GitHub Actions runner log for the session job
D) the GITHUB_TOKEN permissions block in the agent1 workflow


Solutions:

Question # 1
Answer: D
Question # 2
Answer: A
Question # 3
Answer: C,D
Question # 4
Answer: B
Question # 5
Answer: A

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