GitHub Agentic AI Developer (GH-600) Exam Questions 2026
GitHub Agentic AI Developer (GH-600) Exam Questions 2026
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Question 1:
An organization is auditing its agent deployment workflow to ensure compliance with risk management standards. The team must ensure that agent actions are properly categorized and that high-risk operations are appropriately gated. Which two actions correctly implement these guardrails while maintaining system performance?
A. Perform a risk assessment to classify every agent tool capability.
B. Require manual sign-off for every single action the agent performs.
C. Automate low-risk tasks to optimize agent-human collaboration efficiency.
D. Disable all agent write access to prevent unauthorized production changes.
E. Implement conditional execution gates based on the classified action risk.
Answer: A and E.
Explanation:
A. Perform a risk assessment to classify every agent tool capability.
Before actions can be gated effectively, the organization must understand the potential impact of each tool available to the agent. This requires a comprehensive risk assessment that catalogs every tool, API endpoint, and command the agent can invoke and classifies them according to risk level.
Examples include:
Low Risk: Reading documentation, querying data, or generating reports.
High Risk: Modifying database schemas, deploying code to production, or changing infrastructure configurations.
Proper classification establishes the foundation for governance and control mechanisms.
E. Implement conditional execution gates based on the classified action risk.
Once tools and actions are classified, the orchestration engine can enforce dynamic governance policies at runtime.
When an agent invokes a low-risk tool, the execution gate evaluates the classification and allows the action to proceed automatically.
When an agent invokes a high-risk tool, the execution gate intercepts the request, pauses execution, and requires manual human validation before the action can be completed.
This approach balances operational efficiency with strong governance controls.
Incorrect:
B. Require manual sign-off for every single action the agent performs.
Although this approach maximizes oversight, it creates a substantial operational bottleneck. Requiring human approval for every action, including simple read-only or repetitive tasks, significantly reduces system efficiency and undermines the benefits of automation.
C. Automate low-risk tasks to optimize agent-human collaboration efficiency.
Automating low-risk tasks is a valuable operational practice, but it is not a governance guardrail. While it improves efficiency, it does not provide a compliance checkpoint or risk-mitigation mechanism for sensitive actions.
D. Disable all agent write access to prevent unauthorized production changes.
This is an overly restrictive approach that severely limits the usefulness of the agent. Without write access, the agent cannot perform essential functions such as deployments, updates, remediation tasks, or documentation changes, reducing it to a passive monitoring role rather than an active workflow participant.
Question 2:
A project team is refining an agent configuration that interacts with a database schema migration tool. The organization mandates that any agent-initiated schema modification must be preceded by a human-validated plan and an explicit sign-off. However, the agent should handle routine data reporting queries with full autonomy to support rapid dashboard updates. The following configuration snippet outlines the current setup:
{
“agent_name“: “db-manager“,
“operational_mode“: “full_autonomy“,
“restricted_paths“:[“/schema/“],
“human_in_the_loop“: “disabled“
}
If the agent must not execute schema modifications without explicit manual approval, which modification must the team make to the configuration?
A. Change operational_mode to supervised and define approval gates.
B. Update restricted_paths to include all database query directories.
C. Remove the restricted_paths key to allow flexible execution paths.
D. Enable human_in_the_loop globally for all agent operations.
Answer: A
Explanation:
To balance agility with strict system governance, a multi-agent orchestration architecture should move away from a binary "all-or-nothing" execution model. Instead, the agent should operate in a controlled execution mode where conditional validation rules apply.
Establishing Oversight (Supervised Mode)
Changing the operational_mode from full_autonomy to supervised signals to the central orchestrator that the agent's actions are subject to governance controls.
Implementing Risk-Based Approval Gates
By defining targeted approval gates linked to the /schema/ path, the team creates a conditional checkpoint. When the agent attempts a schema migration, the orchestrator intercepts the action, generates the required human-validated plan, and pauses execution until explicit approval is provided.
Preserving Autonomy for Low-Risk Tasks
Because the approval gates apply only to schema modifications, routine data reporting queries that do not interact with the /schema/ path can continue running automatically without creating delays for live dashboards.
The corrected configuration would resemble:
{
"agent_name": "db-manager",
"operational_mode": "supervised",
"restricted_paths": ["/schema/"],
"human_in_the_loop": "enabled_on_restricted",
"approval_gates": [
{
"path": "/schema/*",
"require_approval_from": "database_admin"
}
]
}
Incorrect:
B. Update restricted_paths to include all database query directories
This approach conflicts with the requirement for rapid dashboard updates. If reporting and query directories are also marked as restricted, routine data retrieval operations would require human approval, creating significant operational delays.
C. Remove the restricted_paths key to allow flexible execution paths
Removing path restrictions eliminates the system's ability to distinguish between low-risk read operations and high-risk schema modifications. This would give the agent unrestricted authority to alter database schemas without human oversight.
D. Enable human_in_the_loop globally for all agent operations
Although this would protect schema changes, it applies an unnecessarily broad control across all agent activities. Requiring manual approval for routine reporting and dashboard-related queries undermines the efficiency benefits of autonomous agents and creates avoidable bottlenecks.
Question 3:
An engineer notices the agent consistently attempts to use a file-system search tool on sensitive directories that are excluded from the project‘s scope. The engineer must restrict the tool‘s access to only the designated source code directory. Which action ensures this constraint is applied?
A. Modify the agent instructions to explicitly warn against searching sensitive directories.
B. Define tool scope parameters to limit execution to the specific source directory.
C. Implement a global allow-list filter on the MCP server to block sensitive paths.
D. Update the agent memory to store a blacklist of all restricted directory paths
Answer: B
Explanation:
The most secure and reliable way to restrict an AI agent's behavior is through hard technical constraints at the tool execution level. By explicitly configuring the tool's input parameters or environment scope to allow access only to the designated source directory, the agent is physically prevented from accessing anything outside of it, regardless of its actions or instructions. This enforces the principle of least privilege directly within the system architecture.
Incorrect:
A. Modify the agent instructions to explicitly warn against searching sensitive directories.
This approach relies on prompt engineering to enforce security. While instructions can guide an agent's behavior, large language models can be affected by hallucinations, prompt injections, or may ignore instructions while attempting to complete a task. Security boundaries should never depend solely on agent compliance.
C. Implement a global allow-list filter on the MCP server to block sensitive paths.
Although an allow-list on the Model Context Protocol (MCP) server appears secure, applying it globally is not the best architectural choice. A global filter affects all agents and tools on the server. The requirement is to restrict access for a specific tool within a particular project scope, making a global restriction overly broad and potentially disruptive to other legitimate workflows.
D. Update the agent memory to store a blacklist of all restricted directory paths.
This approach has two significant weaknesses. First, it relies on the agent following stored guidance rather than enforcing a hard technical restriction. Second, maintaining a blacklist is inherently less secure than using an allow-list. New sensitive directories or alternative path formats may not be included in the blacklist, creating opportunities for unauthorized access.
Question 4:
You are configuring a custom agent to manage sensitive security policy updates. The organization requires that all changes affecting protected branches must be mediated by a human-in-the-loop process. You are writing the policy configuration to enforce this constraint.
code
Yaml
policy_definition:
scope: protected_branches
on_action:
type: policy_update
workflow_path:
[MISSING_CONFIGURATION_ELEMENT]
Which configuration value correctly enforces the required human authorization for this workflow?
A. execute_automatically_without_review
B. retry_on_failure_no_human_intervention
C. require_manual_human_authorization_trigger
D. notify_administrator_after_execution_completed
Answer: C
Explanation:
A human-in-the-loop (HITL) process requires an automation system to explicitly halt its workflow at a sensitive point and wait for a manual human action before proceeding.
Because the configuration scope targets protected_branches for policy_update actions, injecting require_manual_human_authorization_trigger ensures the agent cannot autonomously commit changes. It forces the system to pause the pipeline and require manual review and approval from an authorized security professional before continuing.
Incorrect:
A. execute_automatically_without_review
This configuration does the exact opposite of what the organization requires. It grants the custom agent full autonomy to modify sensitive security policies on protected branches without human oversight, creating significant compliance and security risks.
B. retry_on_failure_no_human_intervention
This option configures fault-tolerance behavior (how the agent handles errors), not an authorization mechanism. Additionally, the phrase "no human intervention" ensures that even when failures occur, the workflow bypasses human involvement entirely.
D. notify_administrator_after_execution_completed
This is a reactive notification rather than a proactive control. Although notifying an administrator can improve visibility, it occurs only after execution has already completed. If the agent makes a malicious or incorrect update to a protected branch, the change has already been made before the administrator is notified.
Question 5:
A lead engineer is setting up an agent that performs automated code optimization. The organization mandates that the agent must operate with high autonomy but must trigger an approval flow for any code impacting security-critical modules. The configuration block for the autonomy policy is:
{
“policy_name“: “optimization-guardrails“,
“default_mode“: “autonomous“,
“exception_logic“: {
“target“: “security-critical-modules“,
“required_action“: ____________________
}
}
Which configuration value completes this policy to satisfy the security mandate?
A. “allow_autonomous“
B. “bypass_security“
C. “trigger_human_approval“
D. “auto_merge_only“
Answer: C
Explanation:
The organization requires a balance between high autonomy and strict oversight for sensitive actions.
The configuration sets the default_mode to autonomous, allowing the agent to optimize most of the codebase without manual intervention.
The exception_logic serves as a governance guardrail. By defining the target as security-critical-modules, the required_action must interrupt autonomous execution and involve a human supervisor. Setting this value to trigger_human_approval correctly implements the required human-in-the-loop approval process for security-sensitive changes.
Incorrect:
A. "allow_autonomous"
Using this value would allow the agent to continue operating autonomously even when it encounters security-critical modules. This effectively disables the exception logic and fails to meet the organization's security requirements.
B. "bypass_security"
This option directly contradicts the organization's mandate. Bypassing security checks or approval workflows for critical modules would introduce significant security risks and violate governance and compliance standards.
D. "auto_merge_only"
An auto-merge policy would allow the agent to automatically integrate changes into the main codebase without human review. While this increases automation, it removes the required oversight and creates substantial risk when dealing with security-critical modules.
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Question 6:
You are investigating a reasoning failure in a multi-agent system where one agent provided incorrect code recommendations. To perform effective post-hoc analysis, you must capture the necessary data without destroying the environment state. Which approach is correct?
A. Perform immediate rollback of the deployment to clear memory.
B. Extract agent trace logs before initiating system recovery.
C. Reset agent configuration to default parameters for inspection.
D. Delete temporary workflow artifacts to save storage space.
Answer: B
Explanation:
When an agent experiences a reasoning failure—such as generating incorrect code recommendations due to flawed context, inaccurate assumptions, or faulty prompt logic—the most valuable diagnostic information resides in its execution traces, intermediate tool outputs, and LLM context snapshots.
Extracting agent trace logs before making any changes to the environment preserves the exact internal state, prompt sequences, tool interactions, and variables that contributed to the failure. This information is critical for performing root-cause analysis and understanding why the agent reached an incorrect conclusion.
Incorrect:
A. Perform immediate rollback of the deployment to clear memory.
Immediately rolling back the deployment resets the runtime environment and may remove transient telemetry, cached reasoning chains, and execution state information. As a result, valuable diagnostic evidence can be lost before the issue is properly investigated.
C. Reset agent configuration to default parameters for inspection.
Resetting the configuration removes the specific settings under which the failure occurred, such as operational constraints, system prompts, model parameters, or temperature values. This makes it more difficult to reproduce the issue and identify its underlying cause.
D. Delete temporary workflow artifacts to save storage space.
Temporary workflow artifacts often contain important intermediate outputs, scratchpad data, generated files, and tool response payloads created during execution. Deleting these artifacts removes key pieces of the diagnostic trail and can hinder troubleshooting efforts.
Question 7:
The development team must ensure that any tool utilized by the agent to modify build configurations is properly registered. To prevent unauthorized agent tool execution, the agent must appear in the allow list before tool invocation is permitted.
agent_config:
tools:
- name: build-config-updater
version: 1.0.0
security_policy:
mode: strict
allow_list:
- tool: "version-control-manager"
- tool: "________________________"
A. “all-tools-enabled“
B. “git-history-viewer“
C. “build-config-updater“
D. “external-api-access“
Answer: C
Explanation:
The requirement explicitly states that the tool used by the agent to modify build configurations must be registered in the allow_list before execution is permitted under the strict security policy.
The YAML configuration defines the relevant tool as:
tools:
- name: build-config-updater
version: 1.0.0
To authorize this tool, its exact name must be added to the allow_list. Since allow lists in strict mode require explicit matching, "build-config-updater" is the correct entry.
Incorrect:
A. "all-tools-enabled"
This is a generic string and does not match the name of any tool defined in the configuration. In strict mode, only explicitly approved tool names are permitted. As a result, the agent would still be unable to use the build configuration updater.
B. "git-history-viewer"
Although this may represent a valid development tool, it is not defined in the configuration and does not provide the functionality required to modify build configurations.
D. "external-api-access"
This represents a capability or permission type rather than the specific tool identifier that must be authorized. The allow list requires the exact name of the tool being granted execution privileges, which is "build-config-updater".
Question 8:
A team manages several specialized agents that execute tasks in parallel across the repository. To minimize the blast radius of any single agent error, the team must apply strict scoping. Which approach best achieves this isolation?
A. Scope agents to organization.
B. Route all via approvals.
C. Share repository write access.
D. Scope agents to repositories.
Answer: D
Explanation:
The principle of least privilege is fundamental to minimizing an agent's blast radius. By restricting an agent's access to only the specific repository—or even a specific directory or branch—required for its task, a hard security and operational boundary is established.
If an agent experiences a failure, executes an incorrect command, or becomes compromised, the impact is contained within that repository. This prevents unintended changes from affecting the broader codebase and significantly reduces organizational risk.
Incorrect:
A. Scope agents to organization.
This approach increases rather than decreases the blast radius. Granting organization-wide access provides permissions across multiple repositories, projects, and settings. A single mistake or compromise could impact assets throughout the entire organization.
B. Route all via approvals.
Human-in-the-loop (HITL) approvals are valuable for governing high-risk actions, but they are procedural controls rather than technical access boundaries. Approval workflows do not inherently limit what an agent can access and still rely on human judgment, which can be affected by mistakes or approval fatigue.
C. Share repository write access.
Allowing multiple agents to share broad write access increases the risk of conflicts, race conditions, accidental overwrites, and repository state corruption. It expands the potential impact of an error because one agent's actions can directly affect the work of other agents operating within the same environment.
Question 9:
Your multi-agent CI pipeline frequently fails to identify dependency vulnerabilities, and you need to perform a root cause analysis using existing traces. The workflow uses an Orchestrator and two Research agents. The engineering team requires that post-hoc analysis must identify the exact agent that generated the failure signal without relying on aggregate status codes.
steps:
- name: Identify-Failure
uses: github/copilot-trace-analyzer@v1
with:
trace_level: verbose
scope: repository
- name: Correlate-Signals
uses: github/copilot-signal-correlator@v1
Question: Which configuration adjustment ensures the failure is traced to the specific agent?
A. Configure trace correlation via unique agent IDs.
B. Increase trace sampling rate to full capture.
C. Set trace_level to errors only for performance.
D. Disable scope filtering to capture all events.
Answer: A
Explanation:
The requirement is to identify the exact agent (the Orchestrator, Research Agent 1, or Research Agent 2) that generated a failure signal without relying on aggregate status codes.
In a multi-agent environment, traces and logs from multiple agents can become interleaved. By assigning a unique agent ID to every trace event and configuring the signal correlator to map events back to those IDs, each agent's execution path can be tracked independently. This makes it possible to determine exactly which agent's reasoning, decision, or tool invocation resulted in the missed vulnerability.
Incorrect:
B. Increase trace sampling rate to full capture.
Capturing all traces ensures that no telemetry is lost, but it does not address agent attribution. Without unique agent identifiers, the resulting logs remain interleaved, making it difficult to distinguish which Research agent generated a specific event.
C. Set trace_level to errors only for performance.
Limiting traces to errors removes valuable context, including reasoning steps, prompts, tool interactions, and successful operations that occurred before the failure. In many cases, a missed vulnerability does not generate a system error and instead results from flawed analysis, which an errors-only trace configuration may not capture.
D. Disable scope filtering to capture all events.
Disabling scope filtering broadens telemetry collection to include additional system and platform-level events. While this increases data volume, it does not help identify the specific agent responsible for the failure and may introduce unnecessary noise into the analysis process.
Question 10:
You are designing a multi-agent system where one agent, the Planner, identifies tasks, and another, the Executor, performs them. Some tasks are low-risk documentation updates, while others are high-risk production configuration changes. To balance velocity and safety, you must implement a robust workflow that requires human verification for sensitive operations while allowing speed for routine tasks. You need to ensure that the system remains auditable and that the Executor does not perform unverified sensitive actions. Select two approaches that satisfy these requirements.
A. Classify agent actions by risk level and assign specific autonomy tiers.
B. Route all agent actions through human approval to maximize safety.
C. Implement an explicit authorization gate for actions targeting protected branches.
D. Share agent state across tools to ensure the executor has the latest context.
E. Allow the planner to override executor guardrails to prevent workflow bottlenecks.
Answer: A and C
Explanation:
Correct: A. Classify agent actions by risk level and assign specific autonomy tiers.
This approach directly addresses the requirement to balance speed and safety through a tiered autonomy model.
By categorizing tasks according to their risk level—such as low-risk documentation updates versus high-risk production changes—the system can apply different execution policies based on the potential impact of each action.
This allows the Executor agent to autonomously handle low-risk tasks while ensuring that higher-risk actions receive additional scrutiny and oversight before execution.
Correct: C. Implement an explicit authorization gate for actions targeting protected branches.
This approach addresses the safety and auditability requirements for sensitive operations.
A deterministic authorization gate is placed directly in front of protected resources, such as production branches or environments. Regardless of what the Planner agent recommends, the Executor cannot perform a high-risk or destructive action unless the required approval is obtained.
This creates a reliable, auditable control mechanism that enforces human oversight where it is most needed.
Incorrect:
B. Route all agent actions through human approval to maximize safety.
Although this approach maximizes safety, it fails to maintain operational velocity. Requiring approval for routine tasks such as documentation updates introduces unnecessary delays and reduces the value of automation.
D. Share agent state across tools to ensure the executor has the latest context.
State sharing can improve coordination and contextual awareness, but it is not a security control. An Executor with complete context can still perform unsafe actions if no authorization mechanism prevents them.
E. Allow the planner to override executor guardrails to prevent workflow bottlenecks.
This creates a serious architectural weakness. If the Planner agent can bypass Executor guardrails, a mistaken, compromised, or hallucinating Planner could force unauthorized high-risk changes into production. Execution-layer guardrails should be enforced independently and must not be overridden by other autonomous agents.
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SkillCertPro updates exam questions every 2 weeks.
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SkillCertPro assures 100% pass guarantee in first attempt.