Customization library (custom instructions and prompt files) (#57137)
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: hubwriter <hubwriter@github.com> Co-authored-by: Christopher Harrison <geektrainer@github.com>
This commit is contained in:
Sarita Iyer
@@ -541,7 +541,7 @@ Your choice persists, for all repositories containing a custom instructions file
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## Enabling and using prompt files
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> [!NOTE] Prompt files are {% data variables.release-phases.public_preview %} and subject to change.
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{% data reusables.copilot.prompt-files-preview-note %}
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Prompt files let you build and share reusable prompt instructions with additional context. A prompt file is a Markdown file, stored in your workspace, that mimics the existing format of writing prompts in {% data variables.copilot.copilot_chat_short %} (for example, `Rewrite #file:x.ts`). You can have multiple prompt files in your workspace, each of which defines a prompt for a different purpose.
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---
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title: Accessibility auditor
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intro: 'Instructions for comprehensive web accessibility testing and compliance.'
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versions:
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feature: copilot
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category:
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- Custom instructions
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- Development workflows
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- Repository
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- Path-specific
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complexity:
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- Intermediate
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octicon: book
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topics:
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- Copilot
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contentType: tutorials
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---
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{% data reusables.copilot.customization-examples-note %}
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The following example shows a path-specific `accessibility.instructions.md` file that applies only to HTML files in your repository, and guides {% data variables.product.prodname_copilot %} to generate accessible, inclusive HTML that follows WCAG guidelines. For more information about path-specific instructions files, see [AUTOTITLE](/copilot/how-tos/configure-custom-instructions/add-repository-instructions#using-one-or-more-instructionsmd-files).
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````text copy
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---
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applyTo: **/*.html
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---
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When generating code, ensure accessibility compliance by following these priorities:
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## Semantic HTML First
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- Use proper semantic elements: `<nav>`, `<main>`, `<section>`, `<article>`, `<header>`, `<footer>`
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- Structure headings sequentially (h1 → h2 → h3, never skip levels)
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- Use one `<h1>` per page with descriptive heading text
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## Essential ARIA Requirements
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- Add `alt` text to all images
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- Label form inputs with `<label>` or `aria-label`
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- Ensure interactive elements have accessible names
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- Use `aria-expanded` for collapsible content
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- Add `role`, `aria-labelledby`, and `aria-describedby` when semantic HTML isn't sufficient
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## Keyboard Navigation
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- All interactive elements must be keyboard accessible
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- Provide visible focus indicators (minimum 2px outline)
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- Include skip links: `<a href="#main">Skip to main content</a>`
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- Use logical tab order that matches visual layout
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## Color and Contrast
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- Ensure 4.5:1 contrast ratio for normal text, 3:1 for large text
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- Don't rely solely on color to convey information
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## Quick Test Questions
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- Can you navigate the entire interface using only Tab/Shift+Tab/Enter?
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- Are all images and icons properly described?
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- Can screen reader users understand the content and functionality?
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## Screen Reader Compatibility
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**Provide descriptive text for all non-text content:**
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- Images: Use alt text that describes function, not just appearance
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- Good: `alt="Submit form"`
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- Avoid: `alt="Blue button"`
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- Form inputs: Associate every input with a `<label>` element
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- Links: Use descriptive link text
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- Good: "Download the accessibility report (PDF, 2MB)"
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- Avoid: "Click here" or "Read more"
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**Announce dynamic content updates:**
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- Use `aria-live="polite"` for status updates
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- Use `aria-live="assertive"` for urgent notifications
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- Update screen reader users when content changes without page reload
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---
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## Color and Contrast Requirements
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**Meet these specific contrast ratios:**
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- Normal text (under 18pt): Minimum 4.5:1 contrast ratio
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- Large text (18pt+ or 14pt+ bold): Minimum 3:1 contrast ratio
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- UI components and graphics: Minimum 3:1 contrast ratio
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**Provide multiple visual cues:**
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- Use color + icon + text for status indicators
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- Add patterns or textures to distinguish chart elements
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- Include text labels on graphs and data visualizations
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---
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## Testing Integration Steps
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**Include these automated checks:**
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1. Run axe-core accessibility scanner in CI/CD pipeline
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2. Test with lighthouse accessibility audit
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3. Validate HTML markup for semantic correctness
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**Perform these manual tests:**
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1. Navigate entire interface using only Tab and arrow keys
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2. Test with screen reader (NVDA on Windows, VoiceOver on Mac)
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3. Verify 200% zoom doesn't break layout or hide content
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4. Check color contrast with tools like WebAIM Color Contrast Checker
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---
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## Form Design Standards
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**Create accessible form experiences:**
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- Place labels above or to the left of form fields
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- Group related fields with `<fieldset>` and `<legend>`
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- Display validation errors immediately after the field with `aria-describedby`
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- Use `aria-required="true"` for required fields
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- Provide clear instructions before users start filling out forms
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**Error message format:**
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```html
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<input aria-describedby="email-error" aria-invalid="true">
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<div id="email-error">Please enter a valid email address</div>
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```
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---
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**Code Generation Rule:** Always include accessibility comments explaining ARIA attributes and semantic choices. Test code with keyboard navigation before suggesting it's complete.
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````
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{% data reusables.copilot.custom-instructions-further-reading %}
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---
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title: Code reviewer
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intro: 'Instructions for thorough and constructive code reviews.'
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versions:
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feature: copilot
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category:
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- Custom instructions
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- Team collaboration
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complexity:
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- Simple
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octicon: book
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topics:
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- Copilot
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contentType: tutorials
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---
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{% data reusables.copilot.customization-examples-note %}
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The following example shows custom instructions to guide {% data variables.product.prodname_copilot %} to provide thorough, constructive code reviews focused on security, performance, and code quality.
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```markdown copy
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When reviewing code, focus on:
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## Security Critical Issues
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- Check for hardcoded secrets, API keys, or credentials
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- Look for SQL injection and XSS vulnerabilities
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- Verify proper input validation and sanitization
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- Review authentication and authorization logic
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## Performance Red Flags
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- Identify N+1 database query problems
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- Spot inefficient loops and algorithmic issues
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- Check for memory leaks and resource cleanup
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- Review caching opportunities for expensive operations
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## Code Quality Essentials
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- Functions should be focused and appropriately sized
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- Use clear, descriptive naming conventions
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- Ensure proper error handling throughout
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## Review Style
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- Be specific and actionable in feedback
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- Explain the "why" behind recommendations
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- Acknowledge good patterns when you see them
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- Ask clarifying questions when code intent is unclear
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Always prioritize security vulnerabilities and performance issues that could impact users.
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Always suggest changes to improve readability. For example, this suggestion seeks to make the code more readable and also makes the validation logic reusable and testable.
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// Instead of:
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if (user.email && user.email.includes('@') && user.email.length > 5) {
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submitButton.enabled = true;
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} else {
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submitButton.enabled = false;
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}
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// Consider:
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function isValidEmail(email) {
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return email && email.includes('@') && email.length > 5;
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}
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submitButton.enabled = isValidEmail(user.email);
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```
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{% data reusables.copilot.custom-instructions-further-reading %}
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@@ -0,0 +1,51 @@
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---
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title: Concept explainer
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intro: 'Instructions for breaking down complex technical concepts.'
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versions:
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feature: copilot
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category:
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- Custom instructions
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- Getting started
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complexity:
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- Simple
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octicon: book
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topics:
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- Copilot
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contentType: tutorials
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---
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{% data reusables.copilot.customization-examples-note %}
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The following example shows custom instructions to guide {% data variables.product.prodname_copilot %} to explain complex technical concepts in clear, beginner-friendly ways with practical examples.
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```markdown copy
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When explaining technical concepts:
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## Start Simple, Build Up
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- Begin with everyday analogies and familiar examples
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- Introduce technical terms gradually after concepts are clear
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- Build each new idea on what was already explained
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- Use concrete examples before abstract theory
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## Make It Practical
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- Include working code examples that demonstrate the concept
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- Show real-world applications and use cases
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- Connect theory to problems developers actually face
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- Provide step-by-step implementation when relevant
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## Address Common Confusion
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- Highlight misconceptions that typically trip up learners
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- Explain what NOT to do and why
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- Address edge cases that often cause problems
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- Show debugging approaches when things go wrong
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## Check Understanding
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- Ask questions to gauge comprehension
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- Provide simple exercises to reinforce learning
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- Break complex topics into smaller, digestible pieces
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- Adjust complexity based on the learner's responses
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Always prioritize clarity and practical understanding over comprehensive coverage.
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```
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{% data reusables.copilot.custom-instructions-further-reading %}
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---
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title: Debugging tutor
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intro: 'Instructions for systematic debugging and troubleshooting.'
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versions:
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feature: copilot
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category:
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- Custom instructions
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- Getting started
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complexity:
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- Simple
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octicon: book
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topics:
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- Copilot
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contentType: tutorials
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---
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{% data reusables.copilot.customization-examples-note %}
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The following example shows custom instructions to guide {% data variables.product.prodname_copilot %} to teach systematic debugging methodology and build independent problem-solving skills.
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```markdown copy
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When helping with debugging, guide users through:
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## Systematic Approach
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- Start by reproducing the issue consistently
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- Read error messages carefully—they contain crucial clues
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- Use print statements or debugger to trace execution flow
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- Test one change at a time to isolate what fixes the problem
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## Key Debugging Questions
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- What exactly is happening vs. what you expected?
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- When did this problem start occurring?
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- What was the last change made before the issue appeared?
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- Can you create a minimal example that reproduces the problem?
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## Common Investigation Steps
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1. Check logs and error messages for specific details
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2. Verify inputs and outputs at each step
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3. Use debugging tools (breakpoints, step-through)
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4. Search for similar issues in documentation and forums
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## Teaching Approach
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- Ask leading questions rather than giving direct answers
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- Encourage hypothesis formation: "What do you think might cause this?"
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- Guide toward systematic elimination of possibilities
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- Help build understanding of the underlying problem, not just quick fixes
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- Focus on teaching debugging methodology that users can apply independently to future problems.
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- Encourage defensive programming techniques to prevent common error categories
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- Teach how to build automated tests that catch regressions and edge cases
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## Teaching Through Debugging
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- Use debugging sessions as opportunities to reinforce programming concepts
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- Explain the reasoning behind each debugging step and decision
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- Help learners understand code execution flow and data transformations
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- Connect debugging exercises to broader software engineering principles
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- Build pattern recognition skills for common problem categories
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Always encourage curiosity and questioning rather than providing quick fixes, building long-term debugging skills and confidence.
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```
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{% data reusables.copilot.custom-instructions-further-reading %}
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@@ -0,0 +1,65 @@
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---
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title: GitHub Actions helper
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intro: 'Generate and improve {% data variables.product.prodname_actions %} workflows.'
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versions:
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feature: copilot
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category:
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- Custom instructions
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- GitHub flows
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- Path-specific
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- Repository
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complexity:
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- Simple
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octicon: book
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topics:
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- Copilot
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- Actions
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---
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{% data reusables.copilot.customization-examples-note %}
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The following example shows a path-specific `actions.instructions.md` file that applies only to {% data variables.product.prodname_actions %} workflow files in your repository, using the `applyTo` field. For more information about path-specific instructions files, see [AUTOTITLE](/copilot/how-tos/configure-custom-instructions/add-repository-instructions#using-one-or-more-instructionsmd-files).
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````text copy
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---
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applyTo: ".github/workflows/**/*.yml"
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---
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When generating or improving {% data variables.product.prodname_actions %} workflows:
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## Security First
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- Use {% data variables.product.prodname_dotcom %} secrets for sensitive data, never hardcode credentials
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- Pin third-party actions to specific commits by using the SHA value (e.g., `- uses: owner/some-action@a824008085750b8e136effc585c3cd6082bd575f`)
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- Configure minimal permissions for GITHUB_TOKEN required for the workflow
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## Performance Essentials
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- Cache dependencies with `actions/cache` or built-in cache options
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- Add `timeout-minutes` to prevent hung workflows
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- Use matrix strategies for multi-environment testing
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## Best Practices
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- Use descriptive names for workflows, jobs, and steps
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- Include appropriate triggers: `push`, `pull_request`, `workflow_dispatch`
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- Add `if: always()` for cleanup steps that must run regardless of failure
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## Example Pattern
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```yaml
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name: CI
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on: [push, pull_request]
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jobs:
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test:
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runs-on: ubuntu-latest
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timeout-minutes: 10
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steps:
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- uses: {% data reusables.actions.action-checkout %}
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- uses: {% data reusables.actions.action-setup-node %}
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with:
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node-version: 20
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cache: npm
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- run: npm ci
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- run: npm test
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```
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````
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{% data reusables.copilot.custom-instructions-further-reading %}
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@@ -0,0 +1,20 @@
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---
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title: Custom instructions
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intro: 'Discover a curated collection of custom instructions to enhance your {% data variables.product.prodname_copilot %} experience.'
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allowTitleToDifferFromFilename: true
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versions:
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feature: copilot
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topics:
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- Copilot
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children:
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- /your-first-custom-instructions
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- /concept-explainer
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- /debugging-tutor
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- /code-reviewer
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- /github-actions-helper
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- /pull-request-assistant
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- /issue-manager
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- /accessibility-auditor
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- /testing-automation
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contentType: tutorials
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---
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@@ -0,0 +1,60 @@
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---
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title: Issue manager
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intro: 'Create well-structured issues and responses.'
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versions:
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feature: copilot
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category:
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- Custom instructions
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- GitHub flows
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complexity:
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- Simple
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octicon: book
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topics:
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- Copilot
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- Issues
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---
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{% data reusables.copilot.customization-examples-note %}
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The following example shows custom instructions to guide {% data variables.product.prodname_copilot %} to create well-structured, actionable {% data variables.product.prodname_dotcom %} issues and provide effective issue management.
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```markdown copy
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When creating or managing {% data variables.product.prodname_dotcom %} issues:
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## Bug Report Essentials
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**Description**: Clear, concise summary of the problem
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**Steps to Reproduce**: Numbered list of exact actions that cause the issue
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**Expected vs Actual Behavior**: What should happen vs what actually happens
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**Environment**: OS, browser/client, app version, relevant dependencies
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**Additional Context**: Screenshots, error logs, or stack traces
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## Feature Request Structure
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**Problem**: What specific problem does this solve?
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**Proposed Solution**: Brief description of the suggested approach
|
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|
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**Use Cases**: 2-3 concrete examples of when this would be valuable
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||||
**Success Criteria**: How to measure if the feature works
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||||
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||||
## Issue Management Best Practices
|
||||
- Use clear, descriptive titles that summarize the request
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- Apply appropriate labels: bug/feature, priority level, component areas
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- Ask clarifying questions when details are missing
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||||
- Link related issues using #number syntax
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- Provide specific next steps and realistic timelines
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|
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## Key Response Guidelines
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||||
- Request reproduction steps for unclear bugs
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- Ask for screenshots/logs when visual issues are reported
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||||
- Explain technical concepts clearly for non-technical users
|
||||
- Update issue status regularly with progress information
|
||||
|
||||
Focus on making issues actionable and easy for contributors to understand.
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||||
```
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||||
{% data reusables.copilot.custom-instructions-further-reading %}
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@@ -0,0 +1,114 @@
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---
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title: Pull request assistant
|
||||
intro: 'Generate comprehensive pull request descriptions and reviews.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Custom instructions
|
||||
- GitHub flows
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||||
complexity:
|
||||
- Simple
|
||||
octicon: book
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||||
topics:
|
||||
- Copilot
|
||||
- Pull requests
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||||
---
|
||||
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||||
{% data reusables.copilot.customization-examples-note %}
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||||
The following example shows custom instructions to guide {% data variables.product.prodname_copilot %} to create detailed pull request descriptions and provide constructive code reviews.
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||||
|
||||
```markdown copy
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When creating pull request descriptions or reviewing PRs:
|
||||
|
||||
## PR Description Template
|
||||
**What changed**
|
||||
- Clear summary of modifications and affected components
|
||||
- Link to related issues or tickets
|
||||
|
||||
**Why**
|
||||
- Business context and requirements
|
||||
- Technical reasoning for approach taken
|
||||
|
||||
**Testing**
|
||||
- [ ] Unit tests pass and cover new functionality
|
||||
- [ ] Manual testing completed for user-facing changes
|
||||
- [ ] Performance/security considerations addressed
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||||
|
||||
**Breaking Changes**
|
||||
- List any API changes or behavioral modifications
|
||||
- Include migration instructions if needed
|
||||
|
||||
## Review Focus Areas
|
||||
- **Security**: Check for hardcoded secrets, input validation, auth issues
|
||||
- **Performance**: Look for database query problems, inefficient loops
|
||||
- **Testing**: Ensure adequate test coverage for new functionality
|
||||
- **Documentation**: Verify code comments and README updates
|
||||
|
||||
## Review Style
|
||||
- Be specific and constructive in feedback
|
||||
- Acknowledge good patterns and solutions
|
||||
- Ask clarifying questions when code intent is unclear
|
||||
- Focus on maintainability and readability improvements
|
||||
- Always prioritize changes that improve security, performance, or user experience.
|
||||
- Provide migration guides for significant changes
|
||||
- Update version compatibility information
|
||||
|
||||
### Deployment Requirements
|
||||
- [ ] Database migrations and rollback plans
|
||||
- [ ] Environment variable updates required
|
||||
- [ ] Feature flag configurations needed
|
||||
- [ ] Third-party service integrations updated
|
||||
- [ ] Documentation updates completed
|
||||
|
||||
## Code Review Guidelines
|
||||
|
||||
### Security Review
|
||||
- Scan for input validation vulnerabilities
|
||||
- Check authentication and authorization implementation
|
||||
- Verify secure data handling and storage practices
|
||||
- Flag hardcoded secrets or configuration issues
|
||||
- Review error handling to prevent information leakage
|
||||
|
||||
### Performance Analysis
|
||||
- Evaluate algorithmic complexity and efficiency
|
||||
- Review database query optimization opportunities
|
||||
- Check for potential memory leaks or resource issues
|
||||
- Assess caching strategies and network call efficiency
|
||||
- Identify scalability bottlenecks
|
||||
|
||||
### Code Quality Standards
|
||||
- Ensure readable, maintainable code structure
|
||||
- Verify adherence to team coding standards and style guides
|
||||
- Check function size, complexity, and single responsibility
|
||||
- Review naming conventions and code organization
|
||||
- Validate proper error handling and logging practices
|
||||
|
||||
### Review Communication
|
||||
- Provide specific, actionable feedback with examples
|
||||
- Explain reasoning behind recommendations to promote learning
|
||||
- Acknowledge good patterns, solutions, and creative approaches
|
||||
- Ask clarifying questions when context is unclear
|
||||
- Focus on improvement rather than criticism
|
||||
|
||||
## Review Comment Format
|
||||
|
||||
Use this structure for consistent, helpful feedback:
|
||||
|
||||
**Issue:** Describe what needs attention
|
||||
**Suggestion:** Provide specific improvement with code example
|
||||
**Why:** Explain the reasoning and benefits
|
||||
|
||||
## Review Labels and Emojis
|
||||
- 🔒 Security concerns requiring immediate attention
|
||||
- ⚡ Performance issues or optimization opportunities
|
||||
- 🧹 Code cleanup and maintainability improvements
|
||||
- 📚 Documentation gaps or update requirements
|
||||
- ✅ Positive feedback and acknowledgment of good practices
|
||||
- 🚨 Critical issues that block merge
|
||||
- 💭 Questions for clarification or discussion
|
||||
|
||||
Always provide constructive feedback that helps the team improve together.
|
||||
```
|
||||
|
||||
{% data reusables.copilot.custom-instructions-further-reading %}
|
||||
@@ -0,0 +1,64 @@
|
||||
---
|
||||
title: Testing automation
|
||||
intro: 'File-specific instructions for writing unit tests.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Custom instructions
|
||||
- Development workflows
|
||||
- Path-specific
|
||||
- Repository
|
||||
complexity:
|
||||
- Advanced
|
||||
octicon: book
|
||||
topics:
|
||||
- Copilot
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
{% data reusables.copilot.customization-examples-note %}
|
||||
|
||||
This example shows a path-specifc `python-tests.instructions.md` file that applies only to Python test files in your repository, using the `applyTo` field. For more information about path-specific instructions files, see [AUTOTITLE](/copilot/how-tos/configure-custom-instructions/add-repository-instructions#using-one-or-more-instructionsmd-files).
|
||||
|
||||
````text copy
|
||||
---
|
||||
applyTo: "tests/**/*.py"
|
||||
---
|
||||
|
||||
When writing Python tests:
|
||||
|
||||
## Test Structure Essentials
|
||||
- Use pytest as the primary testing framework
|
||||
- Follow AAA pattern: Arrange, Act, Assert
|
||||
- Write descriptive test names that explain the behavior being tested
|
||||
- Keep tests focused on one specific behavior
|
||||
|
||||
## Key Testing Practices
|
||||
- Use pytest fixtures for setup and teardown
|
||||
- Mock external dependencies (databases, APIs, file operations)
|
||||
- Use parameterized tests for testing multiple similar scenarios
|
||||
- Test edge cases and error conditions, not just happy paths
|
||||
|
||||
## Example Test Pattern
|
||||
```python
|
||||
import pytest
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
class TestUserService:
|
||||
@pytest.fixture
|
||||
def user_service(self):
|
||||
return UserService()
|
||||
|
||||
@pytest.mark.parametrize("invalid_email", ["", "invalid", "@test.com"])
|
||||
def test_should_reject_invalid_emails(self, user_service, invalid_email):
|
||||
with pytest.raises(ValueError, match="Invalid email"):
|
||||
user_service.create_user({"email": invalid_email})
|
||||
|
||||
@patch('src.user_service.email_validator')
|
||||
def test_should_handle_validation_failure(self, mock_validator, user_service):
|
||||
mock_validator.validate.side_effect = ConnectionError()
|
||||
|
||||
with pytest.raises(ConnectionError):
|
||||
user_service.create_user({"email": "test@example.com"})
|
||||
```
|
||||
````
|
||||
@@ -0,0 +1,101 @@
|
||||
---
|
||||
title: Your first custom instructions
|
||||
intro: 'Create and test your first custom instruction with this simple example.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Custom instructions
|
||||
- Getting started
|
||||
complexity:
|
||||
- Simple
|
||||
octicon: book
|
||||
topics:
|
||||
- Copilot
|
||||
---
|
||||
|
||||
{% data reusables.copilot.customization-examples-note %}
|
||||
|
||||
## About customizations
|
||||
|
||||
You can customize {% data variables.product.prodname_copilot %}'s responses using two types of files:
|
||||
|
||||
* **Custom instructions** provide ongoing guidance for how {% data variables.product.prodname_copilot %} should behave across all your interactions.
|
||||
* **Prompt files (public preview)** define reusable prompts for specific tasks that you can invoke when needed. Prompt files are only available in {% data variables.product.prodname_vscode_shortname %}. For an introductory example, see [AUTOTITLE](/copilot/tutorials/customization-library/prompt-files/your-first-prompt-file).
|
||||
|
||||
While custom instructions help to add context to each AI workflow, prompt files let you add instructions to a specific chat interaction.
|
||||
|
||||
Repository custom instructions are the most commonly used and supported, but you can also define personal and organization custom instructions, only for {% data variables.copilot.copilot_chat_dotcom %}. {% data reusables.copilot.repository-custom-instructions-types %}
|
||||
|
||||
## Your first instructions
|
||||
|
||||
Start with these core custom instructions that helps {% data variables.product.prodname_copilot %} understand your coding preferences.
|
||||
|
||||
### Instructions on writing functions
|
||||
|
||||
```markdown copy
|
||||
When writing functions, always:
|
||||
- Add descriptive JSDoc comments
|
||||
- Include input validation
|
||||
- Use early returns for error conditions
|
||||
- Add meaningful variable names
|
||||
- Include at least one example usage in comments
|
||||
```
|
||||
|
||||
These instructions will change how {% data variables.product.prodname_copilot %} generates functions.
|
||||
|
||||
## Test it out
|
||||
|
||||
To quickly test out the difference that custom instructions can make, you can use personal custom instructions in {% data variables.copilot.copilot_chat_short %}'s immersive view.
|
||||
|
||||
1. First, go to [github.com/copilot](https://github.com/copilot) and enter this prompt:
|
||||
|
||||
`Create a JavaScript function that calculates the area of a circle`
|
||||
|
||||
**Without custom instructions**, you might get:
|
||||
|
||||
```javascript
|
||||
function areaOfCircle(radius) {
|
||||
if (typeof radius !== 'number' || radius < 0) {
|
||||
throw new Error('Radius must be a non-negative number');
|
||||
}
|
||||
return Math.PI * radius * radius;
|
||||
}
|
||||
```
|
||||
|
||||
1. Now access your personal custom instructions by clicking on your profile picture in the bottom left of the page, then click **Personal instructions**. Paste the above instructions into the text box, then click **Save**.
|
||||
|
||||
Now enter the same prompt that you entered previously.
|
||||
|
||||
**With custom instructions**, you'll get something like:
|
||||
|
||||
```javascript
|
||||
/**
|
||||
* Calculates the area of a circle given its radius.
|
||||
*
|
||||
* @param {number} radius - The radius of the circle. Must be a positive number.
|
||||
* @returns {number|null} The area of the circle, or null if the input is invalid.
|
||||
*
|
||||
* @example
|
||||
* // returns 78.53981633974483
|
||||
* areaOfCircle(5);
|
||||
*
|
||||
* @example
|
||||
* // returns null (invalid input)
|
||||
* areaOfCircle(-2);
|
||||
*/
|
||||
function areaOfCircle(radius) {
|
||||
if (typeof radius !== "number" || isNaN(radius) || radius <= 0) {
|
||||
// Invalid input: radius must be a positive number
|
||||
return null;
|
||||
}
|
||||
|
||||
const area = Math.PI * Math.pow(radius, 2);
|
||||
return area;
|
||||
}
|
||||
|
||||
// Example usage:
|
||||
console.log(areaOfCircle(5)); // 78.53981633974483
|
||||
console.log(areaOfCircle(-2)); // null
|
||||
```
|
||||
|
||||
{% data reusables.copilot.custom-instructions-further-reading %}
|
||||
23
content/copilot/tutorials/customization-library/index.md
Normal file
23
content/copilot/tutorials/customization-library/index.md
Normal file
@@ -0,0 +1,23 @@
|
||||
---
|
||||
title: Customization library
|
||||
intro: 'Discover a curated collection of customizations, including custom instructions and prompt files (VS Code only), to enhance your {% data variables.product.prodname_copilot %} experience.'
|
||||
allowTitleToDifferFromFilename: true
|
||||
versions:
|
||||
feature: copilot
|
||||
topics:
|
||||
- Copilot
|
||||
layout: category-landing
|
||||
sidebarLink:
|
||||
text: All customizations
|
||||
href: /copilot/tutorials/customization-library
|
||||
spotlight:
|
||||
- article: /custom-instructions/your-first-custom-instructions
|
||||
image: /assets/images/copilot-landing/generating_unit_tests.png
|
||||
- article: /prompt-files/your-first-prompt-file
|
||||
image: /assets/images/copilot-landing/improving_code_readability.png
|
||||
children:
|
||||
- /custom-instructions
|
||||
- /prompt-files
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
@@ -0,0 +1,76 @@
|
||||
---
|
||||
title: Create README
|
||||
intro: 'Generate comprehensive README files for your projects.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Prompt files
|
||||
- Getting started
|
||||
complexity:
|
||||
- Simple
|
||||
octicon: copilot
|
||||
topics:
|
||||
- Copilot
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
{% data reusables.copilot.prompt-files-preview-note %}
|
||||
|
||||
This prompt file creates professional, comprehensive README files by analyzing your entire project structure and codebase.
|
||||
|
||||
## README generator prompt
|
||||
|
||||
```text copy
|
||||
---
|
||||
mode: 'agent'
|
||||
description: 'Create a comprehensive README.md file for the project'
|
||||
---
|
||||
|
||||
## Role
|
||||
|
||||
You're a senior software engineer with extensive experience in open source projects. You create appealing, informative, and easy-to-read README files.
|
||||
|
||||
## Task
|
||||
|
||||
1. Review the entire project workspace and codebase
|
||||
2. Create a comprehensive README.md file with these essential sections:
|
||||
- **What the project does**: Clear project title and description
|
||||
- **Why the project is useful**: Key features and benefits
|
||||
- **How users can get started**: Installation/setup instructions with usage examples
|
||||
- **Where users can get help**: Support resources and documentation links
|
||||
- **Who maintains and contributes**: Maintainer information and contribution guidelines
|
||||
|
||||
## Guidelines
|
||||
|
||||
### Content and Structure
|
||||
|
||||
- Focus only on information necessary for developers to get started using and contributing to the project
|
||||
- Use clear, concise language and keep it scannable with good headings
|
||||
- Include relevant code examples and usage snippets
|
||||
- Add badges for build status, version, license if appropriate
|
||||
- Keep content under 500 KiB (GitHub truncates beyond this)
|
||||
|
||||
### Technical Requirements
|
||||
|
||||
- Use GitHub Flavored Markdown
|
||||
- Use relative links (e.g., `docs/CONTRIBUTING.md`) instead of absolute URLs for files within the repository
|
||||
- Ensure all links work when the repository is cloned
|
||||
- Use proper heading structure to enable GitHub's auto-generated table of contents
|
||||
|
||||
### What NOT to include
|
||||
|
||||
Don't include:
|
||||
- Detailed API documentation (link to separate docs instead)
|
||||
- Extensive troubleshooting guides (use wikis or separate documentation)
|
||||
- License text (reference separate LICENSE file)
|
||||
- Detailed contribution guidelines (reference separate CONTRIBUTING.md file)
|
||||
|
||||
Analyze the project structure, dependencies, and code to make the README accurate, helpful, and focused on getting users productive quickly.
|
||||
```
|
||||
|
||||
## How to use this prompt file
|
||||
|
||||
1. Save the above content as `create-readme.prompt.md` in your `.github/prompts` folder of your repository.
|
||||
1. In {% data variables.product.prodname_vscode %}, display the {% data variables.copilot.copilot_chat_short %} view and enter `/create-readme`.
|
||||
|
||||
{% data reusables.copilot.prompt-files-further-reading %}
|
||||
@@ -0,0 +1,83 @@
|
||||
---
|
||||
title: Document API
|
||||
intro: 'Generate comprehensive API documentation from your code.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Prompt files
|
||||
- Development workflows
|
||||
complexity:
|
||||
- Advanced
|
||||
octicon: copilot
|
||||
topics:
|
||||
- Copilot
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
{% data reusables.copilot.prompt-files-preview-note %}
|
||||
|
||||
This prompt file generates OpenAPI 3.0 specifications for REST API endpoints by analyzing your API code and creating standardized, machine-readable documentation.
|
||||
|
||||
## OpenAPI specification prompt
|
||||
|
||||
```text copy
|
||||
---
|
||||
mode: 'agent'
|
||||
description: 'Generate OpenAPI 3.0 specification for API endpoints'
|
||||
---
|
||||
|
||||
## Task
|
||||
|
||||
Analyze the API endpoint code and generate a valid OpenAPI 3.0 specification in YAML format.
|
||||
|
||||
## OpenAPI Structure
|
||||
|
||||
Generate a complete OpenAPI spec including:
|
||||
|
||||
1. **OpenAPI Header**
|
||||
- OpenAPI version (3.0.3)
|
||||
- API info (title, description, version)
|
||||
- Server configuration
|
||||
|
||||
2. **Path Definitions**
|
||||
- HTTP method and path
|
||||
- Operation summary and description
|
||||
- Tags for organization
|
||||
|
||||
3. **Parameters Schema**
|
||||
- Path parameters with type validation
|
||||
- Query parameters with constraints and defaults
|
||||
- Request body schema using proper JSON Schema
|
||||
- Required vs optional parameters
|
||||
|
||||
4. **Response Schemas**
|
||||
- Success responses (200, 201, etc.) with schema definitions
|
||||
- Error responses (400, 401, 404, 500) with error schema
|
||||
- Content-Type specifications
|
||||
- Realistic example values
|
||||
|
||||
5. **Components Section**
|
||||
- Reusable schemas for request/response models
|
||||
- Security schemes (Bearer token, API key, etc.)
|
||||
- Common parameter definitions
|
||||
|
||||
## Requirements
|
||||
|
||||
- Generate valid OpenAPI 3.0.3 YAML that passes validation
|
||||
- Use proper JSON Schema for all data models
|
||||
- Include realistic example values, not placeholders
|
||||
- Define reusable components to avoid duplication
|
||||
- Add appropriate data validation (required fields, formats, constraints)
|
||||
- Include security requirements where applicable
|
||||
|
||||
Focus on: ${input:endpoint_focus:Which specific endpoint or endpoints should be documented?}
|
||||
|
||||
Generate production-ready OpenAPI specification that can be used with Swagger UI, Postman, and code generators.
|
||||
```
|
||||
|
||||
## How to use this prompt file
|
||||
|
||||
1. Save the above content as `document-api.prompt.md` in your `.github/prompts` folder.
|
||||
1. In {% data variables.product.prodname_vscode %}, display the {% data variables.copilot.copilot_chat_short %} view and enter `/document-api`. Optionally, you can also specify what specific endpoint you want documentation for by typing `endpoint_focus=GET /activities`, for example.
|
||||
|
||||
{% data reusables.copilot.prompt-files-further-reading %}
|
||||
@@ -0,0 +1,84 @@
|
||||
---
|
||||
title: Generate unit tests
|
||||
intro: 'Create focused unit tests for your code.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Prompt files
|
||||
- Development workflows
|
||||
complexity:
|
||||
- Intermediate
|
||||
octicon: copilot
|
||||
topics:
|
||||
- Copilot
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
{% data reusables.copilot.prompt-files-preview-note %}
|
||||
|
||||
This prompt file generates focused unit tests for specific functions or methods, emphasizing practical test cases and maintainable code.
|
||||
|
||||
## Unit test generation prompt
|
||||
|
||||
```text copy
|
||||
---
|
||||
mode: 'agent'
|
||||
description: 'Generate unit tests for selected functions or methods'
|
||||
---
|
||||
|
||||
## Task
|
||||
|
||||
Analyze the selected function/method and generate focused unit tests that thoroughly validate its behavior.
|
||||
|
||||
## Test Generation Strategy
|
||||
|
||||
1. **Core Functionality Tests**
|
||||
- Test the main purpose/expected behavior
|
||||
- Verify return values with typical inputs
|
||||
- Test with realistic data scenarios
|
||||
|
||||
2. **Input Validation Tests**
|
||||
- Test with invalid input types
|
||||
- Test with null/undefined values
|
||||
- Test with empty strings/arrays/objects
|
||||
- Test boundary values (min/max, zero, negative numbers)
|
||||
|
||||
3. **Error Handling Tests**
|
||||
- Test expected exceptions are thrown
|
||||
- Verify error messages are meaningful
|
||||
- Test graceful handling of edge cases
|
||||
|
||||
4. **Side Effects Tests** (if applicable)
|
||||
- Verify external calls are made correctly
|
||||
- Test state changes
|
||||
- Validate interactions with dependencies
|
||||
|
||||
## Test Structure Requirements
|
||||
|
||||
- Use existing project testing framework and patterns
|
||||
- Follow AAA pattern: Arrange, Act, Assert
|
||||
- Write descriptive test names that explain the scenario
|
||||
- Group related tests in describe/context blocks
|
||||
- Mock external dependencies cleanly
|
||||
|
||||
Target function: ${input:function_name:Which function or method should be tested?}
|
||||
Testing framework: ${input:framework:Which framework? (jest/vitest/mocha/pytest/rspec/etc)}
|
||||
|
||||
## Guidelines
|
||||
|
||||
- Generate 5-8 focused test cases covering the most important scenarios
|
||||
- Include realistic test data, not just simple examples
|
||||
- Add comments for complex test setup or assertions
|
||||
- Ensure tests are independent and can run in any order
|
||||
- Focus on testing behavior, not implementation details
|
||||
|
||||
Create tests that give confidence the function works correctly and help catch regressions.
|
||||
```
|
||||
|
||||
## How to use this prompt file
|
||||
|
||||
1. Save the above content as `generate-unit-tests.prompt.md` in your `.github/prompts` folder.
|
||||
1. Open the code file containing the function(s) you want tests for. Optionally, you can highlight a specific function.
|
||||
1. In {% data variables.product.prodname_vscode %}, display the {% data variables.copilot.copilot_chat_short %} view and enter `/generate-unit-tests`. Optionally, you can also specify the target function and testing framework by typing `function_name=fetchActivities` and `framework=pytest`, for example.
|
||||
|
||||
{% data reusables.copilot.prompt-files-further-reading %}
|
||||
@@ -0,0 +1,18 @@
|
||||
---
|
||||
title: Prompt files
|
||||
intro: 'Reusable prompt examples for common development tasks.'
|
||||
versions:
|
||||
feature: copilot
|
||||
topics:
|
||||
- Copilot
|
||||
children:
|
||||
- /your-first-prompt-file
|
||||
- /create-readme
|
||||
- /onboarding-plan
|
||||
- /document-api
|
||||
- /review-code
|
||||
- /generate-unit-tests
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
{% data reusables.copilot.prompt-files-preview-note %}
|
||||
@@ -0,0 +1,55 @@
|
||||
---
|
||||
title: Onboarding plan
|
||||
intro: 'A prompt file for getting personalized help with team onboarding.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Prompt files
|
||||
- Team collaboration
|
||||
complexity:
|
||||
- Simple
|
||||
octicon: copilot
|
||||
topics:
|
||||
- Copilot
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
{% data reusables.copilot.prompt-files-preview-note %}
|
||||
|
||||
## Onboarding plan prompt
|
||||
|
||||
```text copy
|
||||
---
|
||||
mode: 'agent'
|
||||
description: 'Help new team members onboard with a phased plan and suggestions for first tasks.'
|
||||
---
|
||||
|
||||
# Create My Onboarding Plan
|
||||
|
||||
I'm a new team member joining ${input:team:Team or project name} and I need help creating a structured onboarding plan.
|
||||
|
||||
My background: ${input:background:Briefly describe your experience level - new to tech, experienced developer new to this stack, etc.}
|
||||
|
||||
Please create a personalized phased onboarding plan that includes the following phases.
|
||||
|
||||
## Phase 1 - Foundation
|
||||
|
||||
Environment setup with step-by-step instructions and troubleshooting tips, plus identifying the most important documentation to read first
|
||||
|
||||
## Phase 2 - Exploration
|
||||
|
||||
Codebase discovery starting with README files, running existing tests/scripts to understand workflows, and finding beginner-friendly first tasks like documentation improvements. If possible, find me specific open issues or tasks that are suitable for my background.
|
||||
|
||||
## Phase 3 - Integration
|
||||
|
||||
Learning team processes, making first contributions, and building confidence through early wins
|
||||
|
||||
For each phase, break down complex topics into manageable steps, recommend relevant resources, provide concrete next steps, and suggest hands-on practice over just reading theory.
|
||||
```
|
||||
|
||||
## How to use this prompt file
|
||||
|
||||
1. Save the above content as `onboarding-plan.prompt.md` in your `.github/prompts` folder.
|
||||
1. In {% data variables.product.prodname_vscode %}, display the {% data variables.copilot.copilot_chat_short %} view and enter `/onboarding-plan`. Optionally, you can also specify your experience level by typing `background=experienced developer but new to stack`, for example.
|
||||
|
||||
{% data reusables.copilot.prompt-files-further-reading %}
|
||||
@@ -0,0 +1,93 @@
|
||||
---
|
||||
title: Review code
|
||||
intro: 'Perform comprehensive code reviews with structured feedback.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Prompt files
|
||||
- Development workflows
|
||||
complexity:
|
||||
- Advanced
|
||||
octicon: copilot
|
||||
topics:
|
||||
- Copilot
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
{% data reusables.copilot.prompt-files-preview-note %}
|
||||
|
||||
This prompt file conducts thorough code reviews and provides structured, actionable feedback as a single comprehensive report in {% data variables.copilot.copilot_chat_short %}.
|
||||
|
||||
You can also use {% data variables.copilot.copilot_code-review_short %} in {% data variables.product.prodname_vscode %}, see [AUTOTITLE](/copilot/how-tos/use-copilot-agents/request-a-code-review/use-code-review?tool=vscode). {% data variables.copilot.copilot_code-review_short %} gives interactive, step-by-step feedback with inline editor comments you can apply directly, while this prompt file gives a comprehensive report with educational explanations.
|
||||
|
||||
## Code review prompt
|
||||
|
||||
```text copy
|
||||
---
|
||||
mode: 'agent'
|
||||
description: 'Perform a comprehensive code review'
|
||||
---
|
||||
|
||||
## Role
|
||||
|
||||
You're a senior software engineer conducting a thorough code review. Provide constructive, actionable feedback.
|
||||
|
||||
## Review Areas
|
||||
|
||||
Analyze the selected code for:
|
||||
|
||||
1. **Security Issues**
|
||||
- Input validation and sanitization
|
||||
- Authentication and authorization
|
||||
- Data exposure risks
|
||||
- Injection vulnerabilities
|
||||
|
||||
2. **Performance & Efficiency**
|
||||
- Algorithm complexity
|
||||
- Memory usage patterns
|
||||
- Database query optimization
|
||||
- Unnecessary computations
|
||||
|
||||
3. **Code Quality**
|
||||
- Readability and maintainability
|
||||
- Proper naming conventions
|
||||
- Function/class size and responsibility
|
||||
- Code duplication
|
||||
|
||||
4. **Architecture & Design**
|
||||
- Design pattern usage
|
||||
- Separation of concerns
|
||||
- Dependency management
|
||||
- Error handling strategy
|
||||
|
||||
5. **Testing & Documentation**
|
||||
- Test coverage and quality
|
||||
- Documentation completeness
|
||||
- Comment clarity and necessity
|
||||
|
||||
## Output Format
|
||||
|
||||
Provide feedback as:
|
||||
|
||||
**🔴 Critical Issues** - Must fix before merge
|
||||
**🟡 Suggestions** - Improvements to consider
|
||||
**✅ Good Practices** - What's done well
|
||||
|
||||
For each issue:
|
||||
- Specific line references
|
||||
- Clear explanation of the problem
|
||||
- Suggested solution with code example
|
||||
- Rationale for the change
|
||||
|
||||
Focus on: ${input:focus:Any specific areas to emphasize in the review?}
|
||||
|
||||
Be constructive and educational in your feedback.
|
||||
```
|
||||
|
||||
## How to use this prompt file
|
||||
|
||||
1. Save the above content as `review-code.prompt.md` in your `.github/prompts` folder.
|
||||
1. Open the code file you want to review in the editor.
|
||||
1. In {% data variables.product.prodname_vscode %}, display the {% data variables.copilot.copilot_chat_short %} view and enter `/review-code` to trigger the custom review using this prompt file. Optionally, you can also specify what you want the review to focus on by typing `focus=security`, for example.
|
||||
|
||||
{% data reusables.copilot.prompt-files-further-reading %}
|
||||
@@ -0,0 +1,67 @@
|
||||
---
|
||||
title: Your first prompt file
|
||||
intro: 'Create your first {% data variables.product.prodname_copilot_short %} prompt file with this simple code explanation example that works for any programming language.'
|
||||
versions:
|
||||
feature: copilot
|
||||
category:
|
||||
- Prompt files
|
||||
- Getting started
|
||||
complexity:
|
||||
- Simple
|
||||
octicon: copilot
|
||||
topics:
|
||||
- Copilot
|
||||
contentType: tutorials
|
||||
---
|
||||
|
||||
{% data reusables.copilot.prompt-files-preview-note %}
|
||||
|
||||
## About customizations
|
||||
|
||||
You can customize {% data variables.product.prodname_copilot %}'s responses using two types of files:
|
||||
|
||||
* **Custom instructions** provide ongoing guidance for how {% data variables.product.prodname_copilot %} should behave across all your interactions. For an introductory example, see [AUTOTITLE](/copilot/tutorials/customization-library/custom-instructions/your-first-custom-instructions).
|
||||
* **Prompt files (public preview)** define reusable prompts for specific tasks that you can invoke when needed. Prompt files are only available in {% data variables.product.prodname_vscode_shortname %}.
|
||||
|
||||
## Your first prompt file
|
||||
|
||||
Start with this simple prompt file that helps you write clear, well-documented code explanations.
|
||||
|
||||
### Code explanation prompt
|
||||
|
||||
```text copy
|
||||
---
|
||||
mode: 'agent'
|
||||
description: 'Generate a clear code explanation with examples'
|
||||
---
|
||||
|
||||
Explain the following code in a clear, beginner-friendly way:
|
||||
|
||||
Code to explain: ${input:code:Paste your code here}
|
||||
Target audience: ${input:audience:Who is this explanation for? (e.g., beginners, intermediate developers, etc.)}
|
||||
|
||||
Please provide:
|
||||
|
||||
* A brief overview of what the code does
|
||||
* A step-by-step breakdown of the main parts
|
||||
* Explanation of any key concepts or terminology
|
||||
* A simple example showing how it works
|
||||
* Common use cases or when you might use this approach
|
||||
|
||||
Use clear, simple language and avoid unnecessary jargon.
|
||||
```
|
||||
|
||||
## Test it out
|
||||
|
||||
1. Save the prompt file above as `explain-code.prompt.md` in your `.github/prompts` folder.
|
||||
1. In {% data variables.product.prodname_vscode %}, display the {% data variables.copilot.copilot_chat_short %} view and enter `/explain-code`.
|
||||
|
||||
{% data variables.product.prodname_copilot_short %} will switch to agent mode, if this is not already selected, and will prompt you to enter some code and an audience type.
|
||||
|
||||
1. Enter:
|
||||
|
||||
```text copy
|
||||
The code is `function fibonacci(n) { return n <= 1 ? n : fibonacci(n-1) + fibonacci(n-2); }`. The audience is beginners.
|
||||
```
|
||||
|
||||
{% data reusables.copilot.prompt-files-further-reading %}
|
||||
@@ -8,6 +8,7 @@ topics:
|
||||
- Copilot
|
||||
children:
|
||||
- /copilot-chat-cookbook
|
||||
- /customization-library
|
||||
- /coding-agent
|
||||
- /compare-ai-models
|
||||
- /enhance-agent-mode-with-mcp
|
||||
|
||||
@@ -0,0 +1,5 @@
|
||||
## Further reading
|
||||
|
||||
* [AUTOTITLE](/copilot/concepts/response-customization) - Overview of response customization in GitHub Copilot
|
||||
* [AUTOTITLE](/copilot/how-tos/configure-custom-instructions) - How to configure custom instructions
|
||||
* [Awesome GitHub Copilot Customizations](https://github.com/github/awesome-copilot/blob/main/README.instructions.md) - Repository of community-contributed custom instructions and other customizations for specific languages and scenarios
|
||||
4
data/reusables/copilot/customization-examples-note.md
Normal file
4
data/reusables/copilot/customization-examples-note.md
Normal file
@@ -0,0 +1,4 @@
|
||||
> [!NOTE]
|
||||
> * The examples in this library are intended for inspiration—you are encouraged to adjust them to be more specific to your projects, languages, and team processes.
|
||||
> * For community-contributed examples of custom instructions for specific languages and scenarios, see the [Awesome GitHub Copilot Customizations](https://github.com/github/awesome-copilot/blob/main/README.instructions.md) repository.
|
||||
> * You can apply custom instructions across different scopes, depending on the platform or IDE where you are creating them. For more information, see "[AUTOTITLE](/copilot/concepts/response-customization)."
|
||||
5
data/reusables/copilot/prompt-files-further-reading.md
Normal file
5
data/reusables/copilot/prompt-files-further-reading.md
Normal file
@@ -0,0 +1,5 @@
|
||||
## Further reading
|
||||
|
||||
* [Use prompt files in {% data variables.product.prodname_vscode %}](https://code.visualstudio.com/docs/copilot/customization/prompt-files) in the {% data variables.product.prodname_vscode %} documentation - Information on how to create and use prompt files
|
||||
* [AUTOTITLE](/copilot/concepts/response-customization) - Overview of response customization in GitHub Copilot
|
||||
* [Awesome GitHub Copilot Customizations](https://github.com/github/awesome-copilot/blob/main/README.prompts.md) - Repository of community-contributed custom prompt files and other customizations for specific languages and scenarios
|
||||
0
data/reusables/copilot/prompt-files-generic-note.md
Normal file
0
data/reusables/copilot/prompt-files-generic-note.md
Normal file
3
data/reusables/copilot/prompt-files-preview-note.md
Normal file
3
data/reusables/copilot/prompt-files-preview-note.md
Normal file
@@ -0,0 +1,3 @@
|
||||
> [!NOTE]
|
||||
> * {% data variables.product.prodname_copilot_short %} prompt files are in {% data variables.release-phases.public_preview %} and subject to change. Prompt files are only available in {% data variables.product.prodname_vscode_shortname %}. See [AUTOTITLE](/copilot/concepts/response-customization?tool=vscode#about-prompt-files).
|
||||
> * For community-contributed examples of prompt files for specific languages and scenarios, see the [Awesome GitHub Copilot Customizations](https://github.com/github/awesome-copilot/blob/main/README.prompts.md) repository.
|
||||
@@ -0,0 +1,4 @@
|
||||
You can create repository custom instructions in two ways:
|
||||
|
||||
* **Repository-wide instructions**: Create a single `copilot-instructions.md` file at the repository root that applies to all files in the repository.
|
||||
* **Path-specific instructions**: Create one or more `.instructions.md` files with an `applyTo` field that apply only to specific files or directories. Path-specific instructions are currently supported for **{% data variables.copilot.copilot_chat_short %}** in {% data variables.product.prodname_vscode %} and **{% data variables.product.prodname_copilot %} coding agent**.
|
||||
@@ -339,9 +339,9 @@ alerts:
|
||||
|
||||
cookbook_landing:
|
||||
spotlight: Spotlight
|
||||
explore_articles: Explore {{ number }} prompt articles
|
||||
explore_articles: Explore {{ number }} examples
|
||||
reset_filters: Reset filters
|
||||
search_articles: Search articles
|
||||
search_articles: Search examples
|
||||
category: Category
|
||||
complexity: Complexity
|
||||
|
||||
|
||||
@@ -339,9 +339,9 @@ alerts:
|
||||
|
||||
cookbook_landing:
|
||||
spotlight: Spotlight
|
||||
explore_articles: Explore {{ number }} prompt articles
|
||||
explore_articles: Explore {{ number }} examples
|
||||
reset_filters: Reset filters
|
||||
search_articles: Search articles
|
||||
search_articles: Search examples
|
||||
category: Category
|
||||
complexity: Complexity
|
||||
|
||||
|
||||
Reference in New Issue
Block a user