The GitHub Copilot Coding Agent changes how .NET developers get work done. Beyond inline suggestions, it can analyze your repo, plan multi‑step tasks, create issues and pull requests, and carry changes across projects—all in the cloud. In this post, we’ll show two concrete scenarios using the eShopLite sample: automatically creating missing unit tests and implementing a new feature starting from a PRD.

Accelerating .NET Development with GitHub Copilot Coding Agent

The .NET ecosystem continues to evolve, and AI-powered tools are starting to play a key role in how developers build, test, and maintain their applications. One of the most exciting opportunities for .NET developers is the GitHub Copilot Coding Agent.

Unlike the classic Copilot inline completions, the Coding Agent will work on the cloud, and it can take on multi-step tasks, coordinate with GitHub repositories, and even create issues and pull requests on your behalf. This transforms Copilot from being a “pair programmer” into an automation agent that can accelerate repetitive tasks and free you to focus on architecture and innovation.

In this post, we’ll walk through two real-world scenarios using the eShopLite sample solution:

1. Automating unit test creation.
2. Implementing a new feature with a Product Requirements Document (PRD).

Scenario 1: Automating Unit Tests with Copilot

As developers, we know unit tests are critical to maintainable software. But let’s be honest: writing unit tests is not always the most exciting part of the job (I know, that’s maybe just me). That’s where GitHub Copilot Coding Agent can help.

Step 1 – Identify Missing Unit Tests

We start by asking Copilot to analyze the solution and identify gaps in the test coverage.

Prompt used:

Analyze the current solution and propose unit tests to add in the scenario 
[scenarios\01-SemanticSearch].
Make a list of tests where each element has title, description, rationale, 
affectedFiles (paths), testMethodName, testCases (objects with name, arrange, 
act, assert, optional expected), dependencies (to mock), priority 
(High|Medium|Low), and complexity (Small|Medium|Large).
Keep suggestions actionable and use repo-relative file paths.

Step 2 – Review Suggested Tests

Copilot provides a structured proposal with clear rationales and expected outcomes. This helps developers quickly validate whether the suggested tests align with project requirements.

Step 3 – Create GitHub Issue

Once we are satisfied with the list, we instruct Copilot to create a GitHub Issue that contains all the details of the missing unit tests.

Prompt used:

Given the current list of missing unit tests, create a new GitHub issue titled 
"Implement missing Unit Tests".
The new GitHub issue content should describe each missing test to be implemented later.
Show the ID and URL of the new created Issue in the current repository.

👉 Example issue: #47 Implement missing Unit Tests

Step 4 – Assign to Copilot Coding Agent

The last step is to assign the issue to the Copilot Coding Agent. From here, Copilot automatically generates the tests, opens a pull request, and awaits human review.

Prompt used:

assign the new issue to @copilot

👉 Example PR: #48 Add Unit Tests

This workflow reduces the manual burden of writing boilerplate tests and helps ensure consistent test quality across the solution.

Scenario 2: Implementing a Feature with a Mock Payment Server

The second scenario demonstrates how Copilot Coding Agent can go beyond testing and actually implement new functionality. Instead of jumping directly into code, we start with a Product Requirements Document (PRD).

Step 1 – Generate PRD

We ask Copilot to draft a PRD that captures the intent and requirements of adding a mock payment service.

Prompt used:

Create a new Markdown file named `04-PRD_Add_Payment_Mock_Server.md` containing a 
Product Requirements Document (PRD) titled "PRD: Add Mock Payment Server / Payment 
Service to eShopLite".
Keep the document business-focused and concise. Include sections: Purpose, Scope, 
Key success criteria, Quick checklist, Assumptions, High-level design overview, API 
contract summary, Data model summary, Implementation notes, Configuration & local 
defaults, Security & privacy notes, Testing & validation, Acceptance criteria, 
Rollout plan, and Appendix with example request/response JSON.

The generated PRD is not just filler text; it provides actionable details like endpoints, environment variables, and acceptance criteria. This ensures that both developers and stakeholders are aligned before any code is written.

Step 2 – Implement PRD

Once the PRD is approved, we pass it to Copilot Coding Agent to implement the desired features.

Copilot creates the code changes, updates configurations, and even generates UI elements where needed. It will also use MCP tools, like Playwright, to capture screenshots and validate the end-to-end experience.

👉 Example PR: #49 Implement Mock Payment Server

This shows the real potential: using AI to bridge documentation, planning, and execution. Copilot doesn’t just help you type faster—it helps you ship features faster.

Summary

GitHub Copilot Coding Agent represents a shift in how .NET developers can approach productivity.

• For testing, it identifies missing coverage, creates issues, and generates PRs.
• For features, it translates requirements into working code via PRDs.
• For collaboration, it integrates seamlessly with GitHub workflows and pull requests.
• And more!

Instead of replacing developers, it augments their workflow, automating repetitive steps and letting humans focus on creativity, design, and review.

If you’re working with .NET and haven’t tried Copilot Coding Agent yet, now is the perfect time to experiment. And remember, you can customize how the Coding Agent works in your repo with AGENTS.md custom instructions—see the Copilot Coding Agent changelog announcement.

References

• eShopLite sample repository: eShopLite on GitHub
• 10 Microsoft MCP Servers to Accelerate Your Development Workflow: Read the blog post
• Copilot Coding Agent AGENTS.md custom instructions: GitHub Changelog