GH-300 Tests Which Copilot Feature, Setting or Safeguard Fits — Not Prompt Tricks
For developers and administrators using GitHub Copilot daily. Features are the largest domain, so separating agent mode, coding agent, instructions files, exclusions and policies matters more than clever prompting.
Check Your Readiness →Most candidates understand GitHub Copilot (GH-300) concepts — and still fail. This exam tests how you apply knowledge under pressure.
Six domains; the official at-a-glance list repeats the features bullet, treated here as a duplicate. Questions describe a developer or admin goal and ask for the feature, setting or pipeline stage that achieves it. 100 minutes; question count not published, about 60 commonly reported.
Search the organization audit log for the prompt
Audit log events cover administrative actions such as seat assignments and policy changes, not prompt or suggestion content. Seat changes at scale use the Copilot user management REST API, for individual users or whole teams.
Disable Copilot because every plan feeds model training
GitHub states Copilot Business and Enterprise data is not used to train its models. Retention differs by surface, such as IDE completions versus Chat, so check the GitHub Copilot Trust Center rather than assuming one figure.
Add a line telling Copilot to be accurate
Chat history is sent with each new request, so stale turns skew answers. Start a new thread when switching topics, then reference the exact context with #file or #selection instead of letting Chat guess.
Write the longest, most detailed description possible
Use few-shot prompting: put sample inputs and their expected outputs in the prompt itself. State the general goal first, add specific constraints, and split multi-part work into smaller requests that are easier to review.
Reinstall the IDE and the Copilot extension
Check the cheap causes first: sign-in and seat, the per-language enable setting, a content exclusion on those files, firewall or proxy access to GitHub endpoints, then the extension logs for auth or connection errors.
Agent mode runs in your editor session, edits multiple files and asks before running terminal commands. The coding agent is assigned an issue on GitHub, works in the background in a GitHub Actions powered environment and opens a pull request.
Prompt files (.prompt.md) run only when invoked by name. Rules that must apply to every request belong in .github/copilot-instructions.md, or in path-specific .instructions.md files for matching paths. Copilot code review also follows those instructions files.
GitHub documents that IDE edit and agent modes, symlinks and remote filesystems are not covered. Exclusions need Copilot Business or Enterprise, can be set at repository, organization or enterprise level, and take time to propagate; reloading the editor fetches them.
Input filtering screens prompts on GitHub's Copilot proxy before generation. Public code matching, toxicity and vulnerability checks happen in post-processing on the generated output. When matches are allowed, code references show the source repository and license.
Tests that assert whatever the code currently returns encode existing bugs. Derive expected values from requirements, ask Copilot to list edge cases, and use integration tests where mocks would hide service interaction. Request synthetic data, never production records.
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See whether you can pick the right Copilot mode, file and safeguard under GH-300 conditions.