AI for Developers

GitHub Copilot Tips: 15 Tricks Most Developers Don't Know

By AI Free Skills·8 min read·Updated Jun 21, 2026

GitHub Copilot is installed on millions of developer machines, but most people only use it for basic autocomplete. These tips unlock its full potential — from faster coding to better suggestions.

Prompting Tricks

  1. Write comments first — Copilot generates much better code when it understands intent. Write a comment describing what you want, then let it complete.
  2. Be specific in comments — "// Sort users by last login date, most recent first, handle null dates" → better code than "// Sort users"
  3. Use function names as prompts — Name your function descriptively and Copilot will implement it: function calculateShippingCostWithDiscountForPrimeMembers()
  4. Provide examples — Write one example of the pattern you want, and Copilot will continue the pattern for all similar cases.
  5. Open relevant files — Copilot uses open tabs as context. Open related files to improve suggestions.

Keyboard Shortcuts

  1. Tab to accept — Accept the full suggestion
  2. Ctrl+→ (word accept) — Accept one word at a time when you want partial suggestions
  3. Alt+] / Alt+[ — Cycle through alternative suggestions
  4. Ctrl+Enter — Open Copilot panel to see all suggestions at once
  5. Esc — Dismiss a suggestion you don't want

Workflow Tricks

  1. Generate tests from code — Open your source file, then open a test file. Write "test" and Copilot will generate tests based on the source.
  2. Chat for complex tasks — Use Copilot Chat (Ctrl+I) for tasks that need explanation, not just code completion.
  3. Use /fix for errors — Select code with an error, open chat, type /fix. Copilot analyzes and suggests a fix.
  4. Use /explain for learning — Select unfamiliar code, type /explain. Great for onboarding onto new codebases.
  5. Workspace context — Use @workspace in chat to ask questions about your entire codebase, not just the current file.

When Copilot Isn't Enough

Copilot excels at line-by-line coding but has limitations:

  • Complex refactors across multiple files → Use Cursor or Claude Code
  • Architecture decisions → Use AI chat with full project context
  • Debugging complex issues → Use AI with full error context and logs

For AI-assisted development workflows beyond Copilot, browse our Developer Tools prompts.

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