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AI / GitHub Copilot CLI Fundamentals Interview Questions

What are best practices for writing effective prompts in GitHub Copilot CLI?

The quality of Copilot CLI's output is directly related to the clarity and specificity of your prompt. Well-structured prompts reduce back-and-forth and get you to working code faster.

Prompt writing principles
PrincipleExample
Specify the task clearly'Add input validation to the email field in src/forms/signup.tsx - reject addresses without @ and a domain'
Include the context path'Look at src/api/auth.ts and add rate limiting to the /login endpoint'
Mention constraints'Add the feature without modifying existing tests'
Describe the expected outcome'The result should pass all existing tests and add new tests for the validation logic'
Break large tasks into phasesUse Plan mode to review a step-by-step plan before Autopilot executes it
# Vague prompt (avoid)
"Fix the bug"

# Better prompt
"The login form throws a TypeError when the email field is empty.
Fix the bug in src/components/LoginForm.tsx - the issue
is in the handleSubmit function around line 45."

# Best prompt for complex task - use Plan mode
# Shift+Tab to Plan mode, then:
"Refactor the payment processing module in src/payments/ to use
the new Stripe SDK v5 API. The old SDK used client.charges.create();
the new SDK uses client.paymentIntents.create(). Preserve all
existing error handling and update the relevant unit tests."
# → Copilot produces a plan for review before executing

Pro tip - use Plan mode for risky changes: before letting Copilot execute a significant refactor or delete files, switch to Plan mode (Shift+Tab) and review the proposed steps. This catches misunderstandings before they cause unintended changes.

What is the most important quality of an effective Copilot CLI prompt?
Why is it recommended to use Plan mode before executing large refactoring tasks in Copilot CLI?

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