GH-600 Skills Measured — Full Breakdown
By IT-Journey Team
Complete breakdown of all 6 domains and 19 sub-skills for GH-600, each linked to its corresponding quest.
Estimated reading time: 8 minutes
Table of Contents
GH-600 Skills Measured — Full Breakdown
Official source: learn.microsoft.com/credentials/certifications/resources/study-guides/gh-600
Each sub-skill maps to exactly one quest. Click the quest link to start practising that skill immediately.
How to use this page: Work through each domain in order. After reading each sub-skill, rate your confidence (1–5). Return to this page before your exam and ensure every sub-skill is ≥ 4. The Skills Checklist provides a printable version.
Exam Question Archetypes
Understanding the question type is as important as knowing the content. GH-600 uses three primary patterns:
| Archetype | Description | Example stem |
|---|---|---|
| Scenario → Diagnosis | A failing or misbehaving agent is described — identify root cause | “An agent repeatedly requests the same API endpoint. What is the most likely cause?” |
| Config Selection | Choose the YAML/config that satisfies a stated constraint | “Which permissions: block grants the minimum privilege for an agent to open a PR?” |
| Best Practice | Select the most appropriate design decision from four plausible options | “Which guardrail approach best preserves velocity while preventing irreversible file deletions?” |
Keep these archetypes in mind as you read each sub-skill below.
Domain 1 — Prepare Agent Architecture & SDLC Processes (15–20%)
Sub-Skill 1.1 — Integrate agents into the SDLC
- Identify steps for agents to perform
- Identify and mitigate common anti-patterns in agents
- Define inputs, outputs, and success criteria for agents
→ Quest: Q1: Initiation Rites — Embedding Agents in the SDLC
Sub-Skill 1.2 — Define boundaries between planning, reasoning, and action
- Configure agent planning to be distinct from agent execution
- Configure an agent to output a structured plan
- Validate agent plans
- Prevent agent action until the agent checked and approved
→ Quest: Q2: The Three Sigils — Plan, Reason, Act
Sub-Skill 1.3 — Configure observability and control for autonomous agents
- Plan and implement the degree of agent autonomy, including guardrails
- Configure agent to produce inspectable artifacts within standard development tooling
- Configure human intervention for autonomous agents without slowing delivery
→ Quest: Q3: The All-Seeing Eye — Observability & Control
Domain 2 — Implement Tool Use & Environment Interaction (20–25%)
Sub-Skill 2.1 — Select and configure agent tools
- Identify required tools
- Configure agent tools
- Configure agent tool permissions
→ Quest: Q4: Forging the Agent’s Arsenal
Sub-Skill 2.2 — Configure MCP servers
- Add an MCP server as a tool to an agent
- Configure a GitHub remote MCP server
- Configure the MCP registries
- Configure MCP allow lists
→ Quest: Q5: The MCP Conclave
Sub-Skill 2.3 — Integrate agents within development environments
- Evaluate the execution context for an agent
- Configure an agent’s scope to a specific repository
- Configure an agent to be invoked in a CI workflow
- Configure an agent to use branch-based scope
- Enable an agent to perform autonomous actions (branches, PRs)
- Configure an agent to handle environment-specific constraints
→ Quest: Q6: Bind the Agent to the Realm
Sub-Skill 2.4 — Operate agents with safe execution paths and robust error handling
- Implement error handling
- Implement retries
- Implement rollbacks
- Implement escalation paths
- Implement traceability and accountability for agent actions
→ Quest: Q7: The Shield of Retries
Domain 3 — Manage Memory, State & Execution (10–15%)
Sub-Skill 3.1 — Implement agent memory strategies
- Choose between short-term, long-term, and external memory
- Scope agent memory to task-relevant information
- Define memory expiration, pruning, and reset rules
→ Quest: Q8: Vaults of Recollection — Memory Strategies
Sub-Skill 3.2 — Persist agent state and manage context drift
- Capture task progress and decisions as durable artifacts
- Resume agent work without repeating steps or diverging from prior decisions
- Detect and correct drift during extended agent execution
→ Quest: Q9: Anchoring the Drifting Agent
Sub-Skill 3.3 — Ensure continuity of agent memory and state across tools and environments
- Share agent state
- Prevent conflicting context
- Prevent stale context
→ Quest: Q10: Crossing the Tool Planes
Domain 4 — Perform Evaluation, Error Analysis & Tuning (15–20%)
Sub-Skill 4.1 — Define success criteria and evaluation signals for agent tasks
- Specify expected outcomes and operational constraints
- Identify qualitative and quantitative evaluation signals
- Align evaluation criteria with development intent
- Generate evaluation signals by using automated scanning tools
→ Quest: Q11: The Oracle’s Rubric
Sub-Skill 4.2 — Analyze agent failures and identify root causes
- Identify failures using logs, plans, traces, outputs, and workflow artifacts
- Classify root causes: reasoning errors, tool misuse, context/environment issues
→ Quest: Q12: The Necromancer’s Inquest
Sub-Skill 4.3 — Tune agent behavior based on evaluation results
- Revise instructions, workflows, or constraints
- Refine memory usage
- Refine tool usage and tool access
→ Quest: Q13: Reforging the Agent’s Mind
Domain 5 — Orchestrate Multi-Agent Coordination (15–20%)
Sub-Skill 5.1 — Operate and manage multi-agent workflows
- Apply an orchestration pattern to coordinate multiple agents
- Configure agent isolation for parallel execution
- Detect and resolve agent conflicts (overlapping code changes, duplicated effort, contradictory outputs)
→ Quest: Q14: The Council of Many — Orchestration Patterns
Sub-Skill 5.2 — Configure observability for multi-agent behavior
- Configure multi-agent workflows to produce artifacts suitable for review and audit
- Document key decisions, handoffs, and outcomes across agents
- Perform post-hoc analysis of multi-agent behavior
→ Quest: Q15: The Scribe’s Codex — Multi-Agent Observability
Sub-Skill 5.3 — Detect and respond to multi-agent failures and degraded behavior
- Identify failed, partial, or stalled agent executions
- Respond to degraded behavior or coordination across agents
- Implement multi-agent recovery patterns (rollback, human-in-the-loop)
→ Quest: Q16: When Familiars Fall — Failure & Recovery
Sub-Skill 5.4 — Manage the lifecycle of agents within multi-agent workflows
- Add agents to existing multi-agent workflows
- Update, reconfigure, or replace agents without disrupting active workflows
- Retire agents while preserving auditability and workflow continuity
→ Quest: Q17: The Agent Pantheon — Lifecycle Management
Domain 6 — Implement Guardrails & Accountability (10–15%)
Sub-Skill 6.1 — Define autonomy levels
- Classify agent actions by operational, security, and compliance risk
- Assign autonomy levels to maximize delivery speed while remaining compliant
→ Quest: Q18: The Autonomy Scales
Sub-Skill 6.2 — Implement guardrails and human-in-the-loop workflows
- Identify the subset of actions that require human judgment
- Block actions that violate defined security, compliance, or Responsible AI policies
- Scope permissions and execution contexts to enforce least-privilege access
- Require explicit authorization for irreversible or compliance-sensitive changes
- Preserve execution velocity by minimizing approvals that do not materially reduce risk
→ Quest: Q19: The Warden’s Pact — Guardrails & HITL
Coverage Matrix
| GH-600 Sub-Skill | Quest | Level |
|---|---|---|
| 1.1 Integrate agents into SDLC | Q1 | 0111 |
| 1.2 Plan vs. action boundaries | Q2 | 0111 |
| 1.3 Observability & control | Q3 | 1000 |
| 2.1 Select & configure tools | Q4 | 1000 |
| 2.2 Configure MCP servers | Q5 | 1000 |
| 2.3 Dev environment integration | Q6 | 1001 |
| 2.4 Safe execution & error handling | Q7 | 1001 |
| 3.1 Memory strategies | Q8 | 1001 |
| 3.2 State persistence & drift | Q9 | 1010 |
| 3.3 State continuity cross-tools | Q10 | 1010 |
| 4.1 Success criteria & signals | Q11 | 1010 |
| 4.2 Failure root cause analysis | Q12 | 1010 |
| 4.3 Behavior tuning | Q13 | 1011 |
| 5.1 Multi-agent workflows | Q14 | 1011 |
| 5.2 Multi-agent observability | Q15 | 1011 |
| 5.3 Multi-agent failure & recovery | Q16 | 1011 |
| 5.4 Agent lifecycle management | Q17 | 1100 |
| 6.1 Autonomy levels | Q18 | 1100 |
| 6.2 Guardrails & HITL | Q19 | 1100 |
| Capstone | All 6 domains | 1100 |
Coverage: 19/19 (100%) — no gaps, no duplicates.
Domain-by-Domain Exam Tips
Domain 1 — What to watch for
Questions tend to be best-practice selection: given a scenario where an agent is “doing too much” or “acting before planning,” choose the architecture fix. Know the difference between planning output (structured plan artifact) and action execution — and know what a valid “approval gate” looks like.
Domain 2 — What to watch for
The highest-weight domain. Expect config selection questions (MCP server YAML, permissions: blocks, scope constraints) alongside scenario → diagnosis questions where a CI-triggered agent fails silently. Know the exact structure of an MCP tool definition and the allow-list syntax.
Domain 3 — What to watch for
Questions often appear embedded in Domain 4 or 5 scenarios. The key pattern: an agent “forgets” a prior decision — which memory strategy would have prevented it? Understand the difference between short-term context, long-term store, and external memory, and when each is appropriate.
Domain 4 — What to watch for
Expect scenario → diagnosis: a trace or log excerpt is shown, and you must classify the root cause (reasoning error vs tool misuse vs environment issue). Also expect best-practice questions on how to revise instructions vs tool access vs memory when a particular pattern of failure is shown.
Domain 5 — What to watch for
Orchestration questions test whether you can distinguish sequential, parallel, and hierarchical patterns — and when to use each. Failure-recovery questions ask what signal indicates a stalled sub-agent vs a conflicting sub-agent, and how to respond differently.
Domain 6 — What to watch for
The Autonomy Levels Matrix is heavily tested. Be able to classify an action by risk level and select the correct human-in-the-loop gate. Know what “least-privilege” means in the context of agent permissions and how it differs from traditional RBAC.