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GitHub GH-300 Cheat Sheet: Copilot

May 1, 2026

Review GitHub Copilot (GH-300) prompt strategy, context, responsible use, privacy safeguards, feature selection, and productivity traps before practicing in IT Mastery.

On this page

GH-300 is a Copilot decision exam: what context to give, which Copilot feature to use, how to review generated output, and where privacy or organization policy changes the answer. Use this cheat sheet before drilling prompts and Copilot scenarios.

Use this with practice. Review the Copilot checklist, then take the free GH-300 diagnostic or open the full Copilot route in IT Mastery.

Try GH-300 on Web Free GH-300 diagnostic

Exam snapshot

FieldDetail
VendorGitHub
Credential nameGitHub Copilot
Exam codeGH-300
Level shown by Microsoft LearnIntermediate
Exam time shown by Microsoft Learn100 minutes
IT Mastery statusLive GH-300 practice available

Topic map

AreaWhat to knowCommon trap
Responsible AIHuman review, limitations, testing, attribution awareness, and safe usage patternsTreating Copilot output as approved implementation
Copilot featuresChat, completions, explanations, refactoring, tests, PR summaries, CLI help, and feature fitUsing one Copilot feature for every task
Data and architectureContext use, privacy boundaries, content exclusions, and organizational safeguardsAssuming Copilot has access to excluded or unselected context
Prompt and context craftingClear intent, constraints, examples, selected code, repository context, and iterationAsking vague prompts and blaming the feature
Developer productivityDebugging, tests, documentation, code review support, and workflow accelerationPrioritizing speed over correctness, security, or maintainability

Must-know distinctions

DistinctionHow to decide
Completion vs ChatCompletion works inline from local context; Chat supports conversational prompts, explanations, and broader task framing.
Prompt refinement vs code changeRefine the prompt when the answer lacks context; change code when the implementation is actually wrong.
Selected code vs repository contextSelected code gives explicit local context; repository context depends on available files, indexing, and policy.
Productivity aid vs authorityCopilot can draft and suggest; the developer remains responsible for review, tests, and final decisions.
Content exclusion vs prompt hygieneExclusions restrict configured paths; prompt hygiene means users still avoid secrets and sensitive data.
PR summary vs required reviewSummaries help reviewers focus; they do not replace required human approval.
Policy setting vs user behaviorOrganization policy controls availability and safeguards; users still need safe prompting and review discipline.

High-yield checklist

  • State the task goal, constraints, expected output, and relevant files.
  • Include enough code context for Copilot to reason about the real problem.
  • Ask for tests, edge cases, or explanations when correctness matters.
  • Verify API behavior, security-sensitive claims, and policy-sensitive answers against authoritative sources.
  • Keep secrets, customer data, regulated data, and confidential business data out of prompts.
  • Use content exclusions when repository areas should not be available to Copilot.
  • Treat generated code as a draft that needs review, tests, and security checks.
  • Use Copilot Chat for explanation, refactoring plans, debugging hypotheses, and test ideas.
  • Use pull request summaries to accelerate review, not to approve the change.
  • Check organization policy scope before assuming a feature is available.

Common traps

  • Pasting confidential data into a prompt to get a more specific answer.
  • Asking Copilot to decide a licensing, compliance, or production-risk question without verification.
  • Accepting generated code that passes a happy-path test but misses edge cases.
  • Ignoring content exclusions or assuming excluded files influenced an answer.
  • Using Copilot output as evidence that a change is safe.
  • Forgetting that prompt quality often determines answer usefulness.

Practice strategy

Take the free GH-300 diagnostic and tag misses as prompt, feature, privacy, policy, architecture, or responsible-use misses. Then drill the topic that caused the miss. Copilot questions often reward the next responsible action, not the fastest action.

A good GH-300 answer usually follows this sequence: clarify the task, provide context, generate a draft, review critically, test, and keep policy boundaries intact.

Official source

Revised on Monday, May 25, 2026
Privacy and Safeguards
Free Practice Exam