ChatGPT/Copilot Prompt to Master Copilot Chat Slash Commands

What this prompt does

This prompt teaches you to get production-quality results from GitHub Copilot Chat slash commands. You set the [language]/[framework], and the AI shows how to scope code for /explain at [complexity_level] and phrase follow-ups that dig into the why rather than the what, how to feed [error_context] into /fix for accurate fixes instead of generic suggestions, how to select code so /tests generates [test_framework] tests covering edge cases rather than only happy paths, and how to drive /doc toward [doc_style] with proper parameter descriptions and usage examples. It then shows how to chain commands and builds a cheat sheet of [cheat_count] patterns.

The structure works because the gap between a vague prompt and a well-scoped one is the gap between a real fix and pure noise. Including the full [error_context] — the stack trace plus the failing request payload — with /fix is exactly what turns a generic guess into an accurate fix grounded in the actual failure. Scoping a tight code selection before /tests is what produces real edge-case coverage instead of shallow happy-path tests. Chaining /explain into /fix into /tests creates a systematic flow for unfamiliar code: understand it, repair it, then lock the behavior in with tests, so you are never fixing something you do not actually understand. The cheat sheet exists so the strongest patterns are memorable enough that the team uses them without thinking.

When to use it

• You use Copilot Chat daily and want more than vague, generic responses out of it
• You need /fix to produce real fixes by feeding it proper [error_context]
• You want /tests to cover edge cases in [test_framework], not just the happy paths
• You are working through unfamiliar code and want to chain /explain into /fix into /tests
• Your /doc output does not match your [doc_style] and you want patterns that reliably do
• You want a memorizable cheat sheet of the strongest command patterns for your team to share

Example output

You get a practical guide per command: how to select and phrase /explain for deeper why-questions, how to attach [error_context] to /fix, how to scope /tests toward edge cases in [test_framework], and /doc patterns matching [doc_style]. It includes a chained workflow (/explain into /fix into /tests), a few lesser-known commands with their best use cases, and a cheat sheet of [cheat_count] patterns to memorize.

Pro tips

• For /fix, include the full [error_context] — the stack trace plus the failing payload — or you get a generic guess
• Phrase /explain follow-ups around why, not what, to get genuine reasoning rather than a restatement of the code
• Select tight, relevant code before /tests so generated cases target real edge cases instead of trivial paths
• Chain /explain into /fix into /tests on unfamiliar code to keep momentum and avoid fixing what you do not understand
• Set [doc_style] precisely so /doc produces docblocks with the exact tags you actually use
• Keep the [cheat_count] cheat sheet short enough that the team can actually memorize and reach for it