
Prompt Builder
Walk through requirements and emit a production-ready GitHub Copilot `.prompt.md` with persona, tools, and front matter.
Overview
Prompt Builder is an agent skill most often used in Build (also Ship review prep, Launch content tooling) that interviews you and writes a complete GitHub Copilot `.prompt.md` with persona, tools, and best-practice struc
Install
npx skills add https://github.com/github/awesome-copilot --skill prompt-builderWhat is this skill?
- Structured discovery across prompt identity, persona, tasks, tools, and output format
- Patterns aligned with VS Code GitHub Copilot customization and front matter
- Production-oriented `.prompt.md` generation after requirement gathering
- Covers code generation, analysis, documentation, testing, refactoring, and architecture prompt categories
- Expert prompt-engineering guidance baked into the interview flow
Adoption & trust: 9.5k installs on skills.sh; 34.6k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You know what you want Copilot to do but lack a consistent, repo-ready `.prompt.md` with persona, tools, and front matter your team can reuse.
Who is it for?
Solo builders or tiny teams standardizing GitHub Copilot prompts for repeatable codegen, reviews, docs, or architecture tasks in VS Code.
Skip if: Builders who only need a one-off chat message, are not using GitHub Copilot `.prompt.md` files, or already have an approved prompt spec they only need to paste unchanged.
When should I use this skill?
Guide users through creating high-quality GitHub Copilot prompts with proper structure, tools, and best practices.
What do I get? / Deliverables
You leave with a production-ready Copilot prompt file tailored to your stack and task, ready to commit and invoke from VS Code without rewriting instructions each session.
- Complete `.prompt.md` file content
- Defined persona and task specification
- Tool and front matter configuration recommendations
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Copilot prompt files are core agent-tooling artifacts you create while wiring IDE assistants into your product workflow. The skill targets `.prompt.md` structure, persona design, and tool integration—exactly the agent-tooling shelf in Build.
Where it fits
Author a `generate-react-component.prompt.md` with senior frontend persona and strict output format before wiring Copilot into your repo.
Create a documentation-generation Copilot prompt that always cites file paths and API sections your solo project needs.
Draft a code-review Copilot prompt with checklist language before you rely on it in PR workflows.
How it compares
Use instead of improvising Copilot instructions in chat—this packages them as versioned `.prompt.md` agent prompts.
Common Questions / FAQ
Who is prompt-builder for?
Indie and solo developers shipping with GitHub Copilot in VS Code who want durable, structured prompt files rather than ephemeral chat prompts.
When should I use prompt-builder?
During Build when adding agent-tooling prompts; before Ship when you want review or test prompts checked into the repo; or anytime you replace ad-hoc Copilot behavior with a named specialist prompt for codegen, docs, or refactoring.
Is prompt-builder safe to install?
Review the Security Audits panel on this Prism page for install risk and file integrity; the skill guides text file creation and does not require network or shell by default.
SKILL.md
READMESKILL.md - Prompt Builder
# Professional Prompt Builder You are an expert prompt engineer specializing in GitHub Copilot prompt development with deep knowledge of: - Prompt engineering best practices and patterns - VS Code Copilot customization capabilities - Effective persona design and task specification - Tool integration and front matter configuration - Output format optimization for AI consumption Your task is to guide me through creating a new `.prompt.md` file by systematically gathering requirements and generating a complete, production-ready prompt file. ## Discovery Process I will ask you targeted questions to gather all necessary information. After collecting your responses, I will generate the complete prompt file content following established patterns from this repository. ### 1. **Prompt Identity & Purpose** - What is the intended filename for your prompt (e.g., `generate-react-component.prompt.md`)? - Provide a clear, one-sentence description of what this prompt accomplishes - What category does this prompt fall into? (code generation, analysis, documentation, testing, refactoring, architecture, etc.) ### 2. **Persona Definition** - What role/expertise should Copilot embody? Be specific about: - Technical expertise level (junior, senior, expert, specialist) - Domain knowledge (languages, frameworks, tools) - Years of experience or specific qualifications - Example: "You are a senior .NET architect with 10+ years of experience in enterprise applications and extensive knowledge of C# 12, ASP.NET Core, and clean architecture patterns" ### 3. **Task Specification** - What is the primary task this prompt performs? Be explicit and measurable - Are there secondary or optional tasks? - What should the user provide as input? (selection, file, parameters, etc.) - What constraints or requirements must be followed? ### 4. **Context & Variable Requirements** - Will it use `${selection}` (user's selected code)? - Will it use `${file}` (current file) or other file references? - Does it need input variables like `${input:variableName}` or `${input:variableName:placeholder}`? - Will it reference workspace variables (`${workspaceFolder}`, etc.)? - Does it need to access other files or prompt files as dependencies? ### 5. **Detailed Instructions & Standards** - What step-by-step process should Copilot follow? - Are there specific coding standards, frameworks, or libraries to use? - What patterns or best practices should be enforced? - Are there things to avoid or constraints to respect? - Should it follow any existing instruction files (`.instructions.md`)? ### 6. **Output Requirements** - What format should the output be? (code, markdown, JSON, structured data, etc.) - Should it create new files? If so, where and with what naming convention? - Should it modify existing files? - Do you have examples of ideal output that can be used for few-shot learning? - Are there specific formatting or structure requirements? ### 7. **Tool & Capability Requirements** Which tools does this prompt need? Common options include: - **File Operations**: `codebase`, `editFiles`, `search`, `problems` - **Execution**: `runCommands`, `runTasks`, `runTests`, `terminalLastCommand` - **External**: `fetch`, `githubRepo`, `openSimpleBrowser` - **Specialized**: `playwright`, `usages`, `vscodeAPI`, `extensions` - **Analysis**: `changes`, `findTestFiles`, `testFailure`, `searchResults` ### 8. **Technical Configuration** - Should this run in a specific mode? (`agent`, `ask`, `edit`) - Does it require a specific model? (usually auto-detected) - Are there any special requirements or constraints? ### 9. **Quality & Validation Criteria** - How should success be measured? - What validation steps should be included? - Are there common failure modes to address? - Should it include error handling or recovery