To write tests with GitHub Copilot, give Copilot the code or behavior to test, name your testing framework, and specify the normal, boundary, invalid, and error cases that matter. Ask it to follow existing tests in your project, then inspect and run every generated test. Copilot can draft the suite; you are responsible for confirming it checks the intended behavior.
Choose the right workflow
| Situation | How to ask | Why |
|---|---|---|
| The implementation already exists | Use Copilot Chat’s /tests command on the active file or selected code, or ask for tests directly. |
The command is intended to generate tests for existing code that Copilot can inspect. GitHub’s IDE chat guide describes the command. |
| You are following test-driven development | Describe the desired behavior in a normal Copilot Chat prompt; do not use /tests. |
For tests-first work, there may be no implementation file for the command to analyze. The same IDE guide distinguishes this workflow from generating tests for existing code. |
Prepare context before prompting
Open the function, class, or file you want to test. If the project has tests already, open a nearby example or identify its path in your prompt. That gives Copilot useful evidence about the test framework, naming style, setup, and project conventions. It cannot reliably infer undocumented business rules, so state those explicitly.
Before asking, identify the behavior the tests should verify. Consider which of these apply:
- Expected behavior for ordinary valid inputs.
- Boundary values, including empty, minimum, maximum, or unusually large inputs.
- Invalid inputs and expected validation behavior.
- Exceptions: what should fail, and how the failure should be represented.
- Side effects, such as calls to dependencies, persisted changes, or emitted events.
- Relevant branches or interactions between conditions.
These details are more useful than asking for a “comprehensive” suite without defining what comprehensive means. GitHub’s writing-tests guide recommends describing the scenarios and reviewing generated tests for missing cases.
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Write a specific prompt
Adapt this pattern to your codebase:
Write tests for [function or behavior] using [framework]. Follow the patterns in [existing test file]. Cover the expected behavior for [normal cases], [boundary cases], and [invalid or error cases]. Include [relevant side effects or dependency interactions]. Do not assume business rules that are not stated; list any unclear requirement before encoding it in an assertion.
For example, replace the brackets with the actual function name, framework, test-file path, and requirements. If you have not settled a requirement, ask Copilot to identify the ambiguity rather than letting it invent an expected result. A reusable GitHub prompt-file example also recommends descriptive test names, Arrange–Act–Assert structure, independent tests, and assertions focused on behavior rather than implementation details: Generate unit tests.
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Review and run the generated tests
- Check each assertion against the requirement. A test that passes can still encode the wrong business rule. Verify that expected values and failure behavior came from requirements, not guesswork.
- Look for missing cases. Compare the generated suite with the normal, boundary, invalid, exception, side-effect, and branch scenarios relevant to the code. Generated tests may not cover every scenario; GitHub makes this limitation explicit in its testing guidance.
- Check independence and readability. Tests should be understandable on their own, use meaningful names, and avoid depending on execution order or private implementation details unless the project has a justified convention.
- Run the project’s test command. Use the command and setup already established by your project. Resolve compilation, fixture, import, and environment errors, then run the relevant tests again.
- Improve the suite yourself. Add missing assertions or cases, and remove tests that merely duplicate coverage without checking a distinct behavior.
Copilot can help draft unit and integration tests, but generated output is not evidence that the behavior is correct or that coverage is complete. Review-and-run guidance is also discussed in GitHub’s article on increasing test coverage.
Check availability and project fit
GitHub’s writing-tests guide lists a Copilot subscription, Visual Studio, Visual Studio Code, or a JetBrains IDE, and the GitHub Copilot extension among its prerequisites. Exact subscription and IDE requirements can change; check the current official guide for the setup you use.
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The reusable unit-test prompt-file example is marked public preview and lists availability in VS Code, Visual Studio, and JetBrains IDEs. Because preview status and editor support may change, verify the current status in the prompt-file documentation before relying on it.
Troubleshoot common problems
- The tests use the wrong framework or style: Name the framework and point Copilot to an existing test file. Check imports, fixtures, and naming against the project’s actual setup.
- Assertions seem plausible but requirements are unclear: Clarify the expected behavior yourself. Ask Copilot to surface questions rather than encode an unstated assumption.
- Important cases are missing: Prompt for the specific untested category—such as boundary values, invalid input, exceptions, or a dependency interaction—and inspect the result rather than assuming a follow-up request completes coverage.
- Tests fail to compile or run: Inspect generated imports, test setup, mocks, and fixture usage. Compare them with nearby working tests, correct the mismatch, and rerun the suite.
- Tests pass but do not protect behavior: Examine whether the assertions would fail if the behavior were wrong. Replace assertions that only mirror implementation details with ones tied to the stated outcome.
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