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| Section | Weight | Objectives |
|---|---|---|
| Orchestrate multi-agent coordination | 15-20% | - Coordinate multiple agents
|
| Manage memory, state, and execution | 10-15% | - Manage context and memory
|
| Implement tool use and environment interaction | 20-25% | - Manage execution environments
|
| Perform evaluation, error analysis, and tuning | 15-20% | - Improve agent behavior
|
| Implement guardrails and accountability | 10-15% | - Implement governance controls
|
| Prepare agent architecture and SDLC processes | 15-20% | - Define boundaries between planning, reasoning, and action
|
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NEW QUESTION # 95
Your company uses GitHub Copilot Enterprise.
Developers use GitHub Copilot agent mode in Microsoft Visual Studio Code on their laptops and Copilot Chat on github.com when they are away from their laptops.
When switching between environments, the developers notice that agent workflows lose continuity because the tools available in Visual Studio Code are unavailable on github.com.
You need to ensure that the agent tools and state are available consistently across environments and can be used from any device without local setup.
What should you do for each requirement? To answer, drag the appropriate actions to the correct requirements.
Answer:
Explanation:
NEW QUESTION # 96
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 resolve the scoping issue associated to agent1.
What should you do?
Answer: C
Explanation:
Litware identifies the following issues: During two recent sessions, agent1 accessed files in billing-service, which is outside the agent's intended scope.
Creating a fine-grained Personal Access Token (PAT) and storing it as a GitHub Actions repository secret is a highly effective way to restrict a Copilot agent's access. By default, a GitHub Copilot cloud agent's native authentication token is limited strictly to the repository where it is running. However, if your agent utilizes agentic workflows or Model Context Protocol (MCP) integrations that pull broader data, injecting a localized PAT ensures it can never read files outside its explicitly designated scope.
Reference:
https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens
NEW QUESTION # 97
You have a custom agent profile file named test-agent.agent.md that contains the following YAML frontmatter:
---
name: test-agent
description: Custom agent description
tools: ['tool-a', 'tool-b']
---
In the same repository, you have an MCP configuration file named mcp.json.
You need to ensure that the GitHub Model Context Protocol (MCP) server is available to test the agent. The solution must allow only the Copilot toolset.
What should you do?
Answer: C
Explanation:
The copilot/* toolset grants the agent access to the Copilot-provided tools while avoiding unrelated tool groups. This directly meets the requirement to allow only the Copilot toolset for the test agent.
Keeping tool-a and tool-b would expand access beyond the stated requirement. Using github/* would expose the broader GitHub tool group rather than limiting the profile to the Copilot toolset. The MCP configuration retains its server structure; changing the server property name does not configure which tools the agent may use.
Toolsets are an important control surface for specialized agents. They let an architect define a narrow capability set for testing, planning, review, or implementation roles. The selected toolset should still be backed by an available and authorized MCP configuration; naming a toolset does not bypass server authentication or policy restrictions.
Study-guide topics: MCP toolsets, custom agent capabilities, and least-privilege tool access.
NEW QUESTION # 98
You want a reusable, shareable set of instructions that defines a specific persona/workflow (e.g.,
"security reviewer") that developers can invoke on demand in Copilot Chat, rather than instructions applied globally to every session. What should you create?
Answer: B
Explanation:
Prompt files define reusable, invocable prompt templates for specific tasks or personas. Unlike copilot-instructions.md, which applies globally and automatically, prompt files are opt-in and triggered explicitly.
NEW QUESTION # 99
You need to make changes to repo1 to support the planned changes for the agents.
What should you modify?
Answer: D
Explanation:
Repository custom agent profiles belong in .github/agents/ and use Markdown files with agent configuration and instructions. When the intended changes concern the agents' roles, available tools, or operating guidance, these profiles are the appropriate implementation point.
An agent profile provides a durable definition that can be shared with other repository contributors. Keeping that definition under version control makes changes reviewable and enables the team to associate a particular agent configuration with the code revision used during evaluation. This is useful when diagnosing why an agent's behavior changed after its instructions or capabilities were modified.
Editor settings and MCP connection settings address different concerns. They can affect the environment in which an agent operates, but they do not replace the agent's own profile. Changing a server connection is appropriate for transport or authentication requirements; changing an agent profile is appropriate for agent behavior and capability selection.
The source selects C. Its applicability depends on the omitted planned changes actually concerning custom agent configuration.
Study-guide topics: agent profiles, configuration management, and SDLC traceability. Reference: GitHub-Creating custom agents.
NEW QUESTION # 100
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