Microsoft GitHub Agentic AI Developer : GH-600

  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 15, 2026
  • Q & A: 85 Questions and Answers

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About Microsoft GitHub Agentic AI Developer : GH-600 Exam

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Microsoft GH-600 Exam Syllabus Topics:

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

Microsoft GitHub Agentic AI Developer Sample Questions:

1. 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) .copilotignore
B) The agent's GITHUB_TOKEN permissions, configured per workflow/repo policy
C) copilot-instructions.md
D) The /context command


2. You have a GitHub repository that uses GitHub Copilot code review on pull requests.
You plan to add repository-wide code review guidance that will apply to all files.
You need Copilot code review to consistently apply the guidance during pull request reviews.
What should you do?

A) Create a .github/instructions/copilot.instructions.md file.
B) Modify the .github/pull_request_template.md file.
C) Create a .github/copilot-instructions.md file.
D) Update the instructions in the .github/agents/*.agent.md files.


3. You have a multi-agent GitHub Actions workflow that uploads review artifacts for each run.
You discover that some workflow run artifacts are being deleted manually.
You need to use your organization's audit log data to identify which user deleted the artifacts.
Which audit log search filter should you use?

A) operation:remove
B) repo:<org>/<repo>
C) action:workflows.run
D) action:artifact.destroy


4. 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

Drag and Drop Question
You need to implement the security requirements for agent1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.


5. During a Copilot CLI session, an MCP tool call fails because the external service requires re- authentication. What is the most likely resolution path?

A) Re-authenticate the MCP server connector
B) Run /diff to inspect changes
C) Switch to plan mode
D) Run /compact to clear context


Solutions:

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

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