Updated for 2026 Exam Objectives

GH-600 Practice Test

GitHub Certified: Agentic AI Developer

GH-600 tests whether you can actually run GitHub Copilot coding agents safely in production β€” MCP servers, tool permissions, memory, multi-agent coordination, and guardrails β€” not just describe what an agent does.

Our 500 scenario-based questions cover the full GH-600 blueprint across six domains: preparing agent architecture and SDLC processes (planning vs. execution boundaries, anti-patterns, observability), implementing tool use and environment interaction (MCP server configuration, tool permissions, firewall allowlists, safe execution paths), managing memory, state, and execution (short-term vs. long-term memory, context drift, state continuity across tools), performing evaluation, error analysis, and tuning (success criteria, root-cause classification, behavior tuning), orchestrating multi-agent coordination (orchestration patterns, conflict detection, lifecycle management), and implementing guardrails and accountability (autonomy levels, human-in-the-loop policy, least-privilege scoping). Every question is grounded against live docs.github.com and Microsoft Learn documentation, including current 2026 material on Copilot coding agent, Copilot CLI, Copilot Memory, and MCP server governance.

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Your GH-600 exam is in the next 2-4 weeks
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Most successful candidates start practice 2-3 weeks before their exam
Updated for the latest exam blueprint

GH-600 Exam Details

What to expect on exam day

Questions

40

Duration

100 minutes

Passing Score

700

Exam Cost

$165

Exam Domains Covered

Master all topics tested on the GH-600 exam

1

Prepare agent architecture and SDLC processes

2

Implement tool use and environment interaction

3

Manage memory, state, and execution

4

Perform evaluation, error analysis, and tuning

5

Orchestrate multi-agent coordination

6

Implement guardrails and accountability

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5 Free GH-600 Questions

See how ready you are for the GH-600 exam. Each question includes a detailed explanation so you learn as you go.

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Sample GH-600 Practice Questions

10 real questions from the free GH-600bank. Pick an answer in your head, then open β€œShow answer” for the explanation.

  1. 1. A team wants to reduce Copilot cloud agent's exposure to secrets it does not need for a given task. Where does the documented guidance say sensitive data an agent should NOT access should be stored?

    • A. In the pull request description, so the agent can read the secrets directly
    • B. As GitHub Actions variables or secrets outside the agent-accessible scope, reserving agent secrets for data the agent actually needs
    • C. In an environment variable named after the agent, purely for convenience
    • D. In the repository README file, so the agent discovers the secrets automatically
    Show answer

    Correct answer: B

    The guidance recommends storing sensitive data the agent should not need as GitHub Actions variables or secrets, while using dedicated agents secrets and variables at the organization or repository level only for data the agent does require. Putting secrets in a PR description, a conveniently-named environment variable, or a README would expose them to the agent rather than restrict access.

  2. 2. A DevOps engineer has one sprint of capacity to address exactly one anti-pattern before an audit. The agent workflow's GITHUB_TOKEN currently has write access to every repository, though tasks only ever touch one. Separately, recent incidents trace to reviewers approving diffs with no stated rationale, since the PR template has no required plan section. Given that the over-broad token has not yet been implicated in an actual incident while the missing-plan gap already caused two production regressions, which control should the engineer prioritize first, and why does the alternative not address the immediate risk?

    • A. Require a PR-template plan section and review-before-merge first, since the demonstrated incidents trace to planless execution, not to the unused broad token scope
    • B. Scope the GITHUB_TOKEN to least privilege first, since credential exposure is inherently more dangerous than any process gap
    • C. Address both simultaneously by disabling the workflow entirely until the sprint ends
    • D. Neither control matters until the audit begins, since anti-pattern mitigation is assessed during formal audits
    Show answer

    Correct answer: A

    The evidence points to planless execution as the active, demonstrated risk - two regressions traced to unreviewed rationale-free diffs - so the PR-template plan requirement and review-before-merge gate address the proven failure mode first. The broad token scope is a latent over-permissioned-agents risk worth fixing later, but scoping it first would leave the already-demonstrated planless-execution gap unaddressed; disabling the workflow ignores the one-control constraint and stops delivery entirely, and waiting for the audit ignores that regressions are already occurring now.

  3. 3. A team wants agent execution to remain bounded to repository workflows even under a tight deadline, but also wants to avoid adding process overhead for a genuinely low-risk documentation-only change. They are considering letting the agent push documentation fixes directly to the default branch to save review time, while keeping the branch-and-PR requirement for code changes. Does this satisfy the documented plan/act separation model?

    • A. Yes, since documentation edits carry no meaningful execution risk and the documented model explicitly exempts them from the branch-and-PR requirement entirely
    • B. No - action stays bounded to a branch and pull request workflow, not direct default-branch changes; a lighter review process cuts overhead without dropping that boundary
    • C. Yes, as long as the agent first states its plan verbally to a teammate in a quick conversation before pushing any of the changes to the branch
    • D. No, but because default-branch pushes happen to already be technically blocked by GitHub platform rules, regardless of what type of change is involved
    Show answer

    Correct answer: B

    The documented model bounds the act phase to a branch and pull request workflow specifically to keep execution controlled and reviewable, and this boundary is not conditioned on perceived risk level - a faster, lighter review process addresses the overhead concern without removing the branch/PR boundary itself. There is no documented risk-based exemption for documentation-only changes, a verbal plan does not substitute for an inspectable PR-based plan, and the correct reasoning is about the documented model's scope, not merely a platform-level technical restriction.

  4. 4. A team defines success criteria for an agent-driven dependency-remediation task as "the CVE advisory is marked resolved AND no new high-severity secret-scanning alerts are introduced." The agent's change resolves the CVE but its lockfile update also triggers one new high-severity secret-scanning alert from an unrelated transitive dependency. Given both conditions were explicitly required, and the team has a policy against merging any change with an open high-severity secret alert, what should happen to this pull request?

    • A. Merge it immediately, since the primary goal of resolving the CVE was achieved
    • B. Merge it and file the new secret-scanning alert as a separate future task
    • C. Do not merge yet; the compound criterion was not fully met, so someone must resolve the new alert first
    • D. Redefine the success criteria retroactively to drop the secret-scanning condition
    Show answer

    Correct answer: C

    The success criterion was explicitly compound - CVE resolution AND no new high-severity alerts - so partially satisfying it does not meet the bar the team itself defined, and the existing policy against merging with an open high-severity alert reinforces holding the merge. Merging immediately ignores the second explicit condition, filing the alert as unrelated future work still leaves the current change in violation of its own stated criteria, and retroactively redefining criteria to force a pass defeats the purpose of setting success criteria before execution.

  5. 5. By default, can GitHub Copilot cloud agent mark its own draft pull request as "Ready for review" or merge it?

    • A. Yes, for both marking ready and merging
    • B. No - draft pull requests it creates must be reviewed and merged by a human
    • C. Yes, for marking ready but not for merging
    • D. Yes, if the repository has fewer than 10 contributors
    Show answer

    Correct answer: B

    Documentation states draft pull requests created by Copilot cloud agent must be reviewed and merged by a human, and the agent cannot mark its pull requests as "Ready for review" or approve or merge them. There is no repository-size exception to this control.

Show 5 more questions
  1. 6. A team adapts the documented implementation-planner agent template for a data-migration project. They want the plan to clearly separate what is in scope for this release from ideas the team is intentionally deferring, without inventing a new section outside the documented template. Which existing section should capture the deferred ideas?

    • A. Considerations
    • B. Not Included
    • C. Technical Approach
    • D. Overview
    Show answer

    Correct answer: B

    The documented template's Not Included section is specifically for future features and nice-to-haves that are intentionally out of scope, matching the deferred-ideas requirement without inventing a new section. Considerations covers assumptions, constraints, and risks for the in-scope work; Technical Approach covers architecture and design trade-offs; and Overview covers the problem statement and success criteria - none are the documented home for deferred scope.

  2. 7. Which of the following is an example of an evaluation signal the plan→act→evaluate lifecycle says should ground how an agent's plan is judged as successful?

    • A. The agent's own stated confidence level in its plan
    • B. How quickly the agent produced the plan
    • C. The total number of files the plan proposes to touch
    • D. Workflow runs and status checks such as build, test, and lint results
    Show answer

    Correct answer: D

    The lifecycle model grounds evaluation in system signals such as workflow runs, status checks, code review feedback, and security scanning results - explicitly not in the agent's own confidence. Speed of plan production and raw file count are not documented evaluation signals for judging whether a plan succeeded.

  3. 8. A team wants agent-generated pull requests to still move quickly through review without weakening security oversight. Which documented practice achieves both goals for a typical, low-risk change?

    • A. Rely on the default code-quality and security validation, which runs without a separate Advanced Security license, alongside normal review
    • B. Disable the automated security validation entirely to reduce review time
    • C. Require each change, regardless of risk, to pass a dedicated four-person committee
    • D. Allow the agent to self-approve low-risk changes, skipping human review
    Show answer

    Correct answer: A

    Documentation states Copilot cloud agent checks the code it generates for security issues by default and does not require a GitHub Secret Protection or Advanced Security license for this validation, letting typical changes move through normal human review without added licensing friction. Disabling validation trades away oversight, a mandatory four-person committee for every change slows delivery unnecessarily, and self-approval contradicts the documented human-approval requirement.

  4. 9. An administrator investigating an agent-authored commit needs to trace the full reasoning session that produced it, not just the diff. Given the documented commit-attribution model, where should they look first?

    • A. The organization's billing dashboard
    • B. The commit message for that agent-authored commit, which includes a link to the agent session logs
    • C. The repository's branch protection settings page
    • D. The agent's marketplace listing page
    Show answer

    Correct answer: B

    The documented model states the commit message for each agent-authored commit includes a link to the agent session logs, giving administrators a direct path from the commit to the full session trace. Billing dashboards, branch protection settings, and a marketplace listing page do not contain session-level reasoning logs.

  5. 10. A platform team is mapping where GitHub Copilot agents can contribute across the SDLC. Which activity is described as an agent task that runs with less need for direct human intervention?

    • A. Deciding the company's overall product roadmap
    • B. Negotiating a vendor contract for a third-party API
    • C. Running an asynchronous background task, such as fixing a backlogged issue
    • D. Approving a pull request for production release
    Show answer

    Correct answer: C

    Documentation describes agents as capable of performing asynchronous tasks, such as running tests or fixing backlog issues, with less need for human intervention. Roadmap decisions, vendor negotiations, and production approvals are governance and business decisions that stay with accountable humans.

Why Practice with MSCertQuiz?

Microsoft Learn teaches concepts. We prepare you for the actual exam.

1

Deep coverage of the tool-and-MCP domain most candidates underestimate: MCP server configuration and registries, Copilot CLI allow/deny tool precedence, firewall allowlist categories, and the COPILOT_MCP_ secret-naming convention

2

Real operational scenarios on memory and state β€” short-term vs. long-term vs. external memory, context-drift detection, and state continuity across tools β€” the details that separate hands-on practitioners from those who only know agent theory

3

Guardrail and accountability content most free question banks skip entirely: autonomy-level classification, least-privilege scoping, and human-in-the-loop policy design for irreversible or compliance-sensitive actions

4

Every question verified against a live-fetched docs.github.com or Microsoft Learn page before it ships, so content stays accurate as GitHub's agentic AI platform keeps shipping

Not sure if you're ready for the GH-600 exam?

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What Our Users Say

β€œThe MCP server and tool-permission questions were exactly what tripped me up when I first configured Copilot coding agent for our team. Practicing scenario after scenario here made the firewall and allowlist rules click before exam day.”

JP

Jamie P.

GH-600 Certified

β€œI use Copilot agents daily but had never thought carefully about memory scoping or context drift across long tasks. The memory and state domain filled real gaps in my knowledge. Passed on my first attempt.”

AV

Ana V.

Platform Engineer

β€œThe multi-agent coordination and guardrail questions were much closer to real production governance decisions than anything else I tried. The explanations actually taught the reasoning, not just the answer.”

CB

Chris B.

Passed GH-600 first try

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Our practice questions are aligned with official Microsoft exam objectives. We recommend studying with Microsoft Learn first, then using MSCertQuiz to test your readiness.

View Official GH-600 Exam Details

GH-600 Frequently Asked Questions

Everything you need to know about the GH-600 Agentic AI certification

What is GH-600?
GH-600 (Developing in Agentic AI Systems) is a certification, provided by Microsoft and maintained by GitHub, for practitioners who operate, integrate, supervise, and govern AI agents inside production-grade SDLC workflows and development environments β€” using GitHub as the system of record and control plane for reliability, safety, and velocity.
How much does the GH-600 exam cost and how long is it?
The GH-600 exam costs $165 USD, runs approximately 100 minutes, and has a passing score of 700 out of 1000. Exact pricing, duration, and question count are set by Microsoft/GitHub at scheduling time β€” confirm current figures on the official certification page before booking, since this is a newer exam.
What is the passing score for GH-600?
The passing score for GH-600 is 700 out of 1000, the same threshold used across nearly all Microsoft and GitHub role-based certification exams. Scoring is scaled, so 700 represents roughly 70% competency spread across all six exam domains rather than a simple raw percentage.
What topics are covered on GH-600?
GH-600 covers six domains: Prepare agent architecture and SDLC processes (15-20%) β€” integrating agents into the SDLC, planning vs. execution boundaries, observability and control; Implement tool use and environment interaction (20-25%) β€” tool configuration, MCP servers, repository and CI scoping, safe execution and error handling; Manage memory, state, and execution (10-15%) β€” memory strategies, state persistence, context-drift correction; Perform evaluation, error analysis, and tuning (15-20%) β€” success criteria, root-cause analysis, behavior tuning; Orchestrate multi-agent coordination (15-20%) β€” orchestration patterns, conflict detection, agent lifecycle management; and Implement guardrails and accountability (10-15%) β€” autonomy levels, human-in-the-loop workflows, least-privilege scoping.
How hard is GH-600?
GH-600 is a scenario-heavy Associate exam that expects hands-on experience running Copilot coding agent and MCP servers in real repositories, not just familiarity with agent terminology. Candidates who have only experimented with agents casually often find the memory/state and multi-agent orchestration domains the hardest, since they require operational judgment most personal projects never exercise.
How long should I study for GH-600?
Candidates already running Copilot coding agent and MCP servers in production repositories, with real experience configuring tool permissions and guardrails, should plan 3-5 weeks, focused on the multi-agent coordination and evaluation domains. Candidates newer to agentic development should plan 6-8 weeks. We recommend working through GitHub's own Copilot documentation first, then practicing with 500 scenario-based questions spread across all six domains in proportion to their exam weight.
What are the prerequisites for GH-600?
There are no enforced prerequisites to register for GH-600, but it is designed for candidates with experience in the software development lifecycle, GitHub workflows and controls, code quality and security review practices, and hands-on use of coding agents including GitHub Copilot, MCP servers, and agent customization (custom instructions, custom agents, tools, and Copilot setup steps).
Who should take GH-600?
GH-600 is aimed at developers, platform engineers, and DevOps engineers who operate, supervise, and govern AI coding agents inside their organization's SDLC β€” working closely with architects, application developers, product managers, and security engineers. It pairs well with GH-200 (GitHub Actions) as a CI/CD-automation companion and AI-500 (Multi-Agent AI) for candidates building a broader agentic-AI credential portfolio.

Also Preparing For

Candidates studying GH-600 often prepare for these certifications next.