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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare agent architecture and SDLC processes | 15–20% | - Integrate agents into the software development lifecycle (SDLC)
|
| Topic 2: Implement tool use and environment interaction | 20–25% | - Select and configure agent tools
|
| Topic 3: Perform evaluation, error analysis, and tuning | 15–20% | - Analyze agent failures and identify root causes
|
| Topic 4: Implement guardrails and accountability | 10–15% | - Implement guardrails and human-in-the-loop workflows
|
| Topic 5: Manage memory, state, and execution | 10–15% | - Persist agent state and manage context drift
|
| Topic 6: Orchestrate multi-agent coordination | 15–20% | - Operate and manage multi-agent workflows
|
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NEW QUESTION # 56
Hotspot Question
You have a GitHub repository that uses the following GrtHub Copilot CLI command in a Bash script.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Yes
Setting --max-autopilot-continues 10 acts as a hard ceiling, preventing infinite loops by cutting off the execution the moment it reaches the 10-step limit.
Box 2: Yes
This command will allow the agent to use all local tools without prompting you for permission.
The --yolo flag is a built-in alias in the official GitHub Copilot CLI. It bypasses safety confirmation prompts by combining three specific permission-granting arguments: --allow-all-tools, --allow-all- paths, and --allow-all-urls.
Box 3: No
This specific command will not allow targeted human intervention at key decision points because it explicitly strips away all prompt checkpoints The options configuration used in your script forces the GitHub Copilot CLI to bypass user confirmation entirely and execute the objective fully autonomously Reference:
https://pub.towardsai.net/i-stopped-prompting-github-copilot-and-started-delegating-to-it-fe2f12a21709?gi=fbf268b2a564
https://docs.github.com/en/copilot/concepts/agents/copilot-cli/autopilot
NEW QUESTION # 57
Hotspot Question
Your company uses GitHub Copilot custom agents in Microsoft Visual Studio Code.
The company also uses the Copilot coding agent on GitHub issues.
You have a file named .planner.agent.md that defines an agent named planner.planner has tools set to ['search', 'read', 'fetch']. There are explicit instructions NOT to write or modify any code. The file also defines a handoff labeled Start Implementation to an agent named implementer and sets send to false.
Developers report that after the planner agent produces a plan, implementation sometimes starts immediately in the same conversation, and code changes appear without an explicit agent switch.
When Copilot-created pull requests stall, maintainers review the pull request timeline and session logs. Several stalled sessions show outbound network commands blocked by a firewall, and the repositories do NOT contain a .github/copilot-instructions.md file.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: No
The configuration of the planner agent alone does not explicitly or fully prevent code changes from being produced automatically in the same conversation.
Box 2: No
No, removing the search tool will not resolve the issue, because the planner agent is not the one executing the network requests or writing the code.
The underlying problem is that the handoff configuration has an logic error (send: false), which prevents a clean, explicit agent migration. Because of this, the implementer agent takes over implicitly within the same conversation session, executing background code changes and attempting blocked internet calls.
Box 3: No
No, adding a .github/copilot-instructions.md file demanding tests and linters will not mitigate the stalled pull requests.
The root cause of your stalling pull requests is an underlying network connectivity issue, not a procedural omission by the agent.
Reference:
https://docs.github.com/en/copilot/concepts/agents/cloud-agent/about-custom-agents
NEW QUESTION # 58
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?
Answer: C
Explanation:
To apply repository-wide code review guidance that consistently impacts all pull request reviews, you must create a .github/copilot-instructions.md file in the root directory of your repository.
GitHub Copilot code review automatically ingests this file to use as a persistent checklist for every file change it analyzes.
Reference:
https://docs.github.com/en/copilot/how-tos/copilot-on-github/customize-copilot/add-custom-instructions/add-repository-instructions
NEW QUESTION # 59
You want to prevent GitHub Copilot from ever suggesting completions or making edits inside a directory containing sensitive credentials templates. What should you configure?
Answer: A
NEW QUESTION # 60
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 configure agent1 to support the planned changes.
What should you do?
Answer: A
Explanation:
Scenario: 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.
The correct action to take is to delete the line with tools: ['read','cearch','edit'] from the agent configuration.
Enabling All Tools: In GitHub Copilot Agent configuration specifications, omitting the tools key entirely or deleting it allows the agent to automatically inherit and utilize all available tools in the runtime environment. Explicitly hardcoding a restricted array limits its capabilities.
Targeted Instructions: Modifying the repository's configuration for the agent ensures that the specific product-api guidelines apply strictly to that custom agent without bleeding into general Copilot Chat or standard Copilot code reviews.
Reference:
https://docs.github.com/en/copilot/how-tos/copilot-sdk/features/mcp
NEW QUESTION # 61
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