Prompts
Copilot autocompleting your habits, or Copilot following your standards?
The difference between Copilot quietly autocompleting whatever pattern it has seen most and Copilot actually following your team's standards comes down to one file most repos never write.
Last updated Aug 15 · 11 min read
Repository instructions: the file that changes every suggestion
GitHub Copilot reads a repository-level instructions file and applies it to every suggestion across the codebase, not just the current file — which means writing it once changes Copilot's default behaviour project-wide rather than requiring every developer to repeat the same correction in every chat. The GitHub Copilot prompt library's foundational entry, authoring a repo instructions file, is built around exactly this leverage — a small amount of writing, applied everywhere.
For a monorepo or a project with genuinely different conventions in different directories, path-scoped instructions apply different rules to different parts of the codebase, rather than forcing one global instruction set to fit every directory equally badly.
Chat modes and reusable prompt files
A custom chat mode configures Copilot Chat for a specific recurring context — building one means not re-explaining that context every session. A reusable prompt file does the same for a specific recurring task, and task-specific generation instructions narrow default suggestions for one well-defined kind of task rather than leaving Copilot to infer intent from context alone.
From issue to plan to scoped agent task
Copilot Workspace turning a raw GitHub issue into an actual implementation plan — that specific workflow — and a properly scoped issue for the Coding Agent — writing one — both address the same underlying problem: an agent given a vague issue produces a vague, hard-to-review result. A tight brief for Agent mode specifically — a task brief template — and a migration plan for Copilot Edits — that template — cover the same principle applied to two more specific workflows.
Debugging, testing and code review, done with Copilot Chat
Pasting a raw stack trace into Copilot Chat often works better with a structured framing — debugging from a stack trace — and chaining explain, fix and test generation together as one flow rather than three separate disconnected asks is what the slash-command chain prompt covers. For review specifically, focusing Copilot's attention on genuine risk in a diff rather than a generic pass over every line is what the code-review risk-focus prompt does, alongside a dedicated accessibility review prompt and an edge-case test suite generator.
Terminal, screenshots, and picking the right model
Copilot in the terminal explaining a command before you run it — that workflow — and turning a screenshot directly into code — the vision-to-code prompt — both lean on Copilot capabilities many developers never try. And since Copilot now supports picking between different underlying models, a model-picker task-fit guide helps match the model choice to the actual task rather than defaulting to whichever one is currently selected.
When Copilot's setup needs to be a real team standard
Individual prompts help one developer. Getting repo instructions, chat modes and Agent conventions set up consistently across a whole team is a bigger process decision. That's exactly what Scult's software team helps establish, or book a meeting to talk through your team's current setup.
Need this built into your business?
The free tools and prompts on this site handle the small, solved problems. If what you need is bigger — custom software, built and maintained for you — that's Scult's day job.
