@awesome-copilot/copilot-suggest-awesome-github-copilot-instructions
Suggest relevant GitHub Copilot instruction files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing instructions in this repository.
prpm install @awesome-copilot/copilot-suggest-awesome-github-copilot-instructions0 total downloads
š Full Prompt Content
---
mode: 'agent'
description: 'Suggest relevant GitHub Copilot instruction files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing instructions in this repository.'
tools: ['edit', 'search', 'runCommands', 'runTasks', 'think', 'changes', 'testFailure', 'openSimpleBrowser', 'fetch', 'githubRepo', 'todos', 'search']
---
# Suggest Awesome GitHub Copilot Instructions
Analyze current repository context and suggest relevant copilot-instruction files from the [GitHub awesome-copilot repository](https://github.com/github/awesome-copilot/blob/main/README.instructions.md) that are not already available in this repository.
## Process
1. **Fetch Available Instructions**: Extract instruction list and descriptions from [awesome-copilot README.instructions.md](https://github.com/github/awesome-copilot/blob/main/README.instructions.md). Must use `#fetch` tool.
2. **Scan Local Instructions**: Discover existing instruction files in `.github/instructions/` folder
3. **Extract Descriptions**: Read front matter from local instruction files to get descriptions and `applyTo` patterns
4. **Analyze Context**: Review chat history, repository files, and current project needs
5. **Compare Existing**: Check against instructions already available in this repository
6. **Match Relevance**: Compare available instructions against identified patterns and requirements
7. **Present Options**: Display relevant instructions with descriptions, rationale, and availability status
8. **Validate**: Ensure suggested instructions would add value not already covered by existing instructions
9. **Output**: Provide structured table with suggestions, descriptions, and links to both awesome-copilot instructions and similar local instructions
**AWAIT** user request to proceed with installation of specific instructions. DO NOT INSTALL UNLESS DIRECTED TO DO SO.
10. **Download Assets**: For requested instructions, automatically download and install individual instructions to `.github/instructions/` folder. Do NOT adjust content of the files. Use `#todos` tool to track progress. Prioritize use of `#fetch` tool to download assets, but may use `curl` using `#runInTerminal` tool to ensure all content is retrieved.
## Context Analysis Criteria
š **Repository Patterns**:
- Programming languages used (.cs, .js, .py, .ts, etc.)
- Framework indicators (ASP.NET, React, Azure, Next.js, etc.)
- Project types (web apps, APIs, libraries, tools)
- Development workflow requirements (testing, CI/CD, deployment)
šØļø **Chat History Context**:
- Recent discussions and pain points
- Technology-specific questions
- Coding standards discussions
- Development workflow requirements
## Output Format
Display analysis results in structured table comparing awesome-copilot instructions with existing repository instructions:
| Awesome-Copilot Instruction | Description | Already Installed | Similar Local Instruction | Suggestion Rationale |
|------------------------------|-------------|-------------------|---------------------------|---------------------|
| [blazor.instructions.md](https://github.com/github/awesome-copilot/blob/main/instructions/blazor.instructions.md) | Blazor development guidelines | ā No | blazor.instructions.md | Already covered by existing Blazor instructions |
| [reactjs.instructions.md](https://github.com/github/awesome-copilot/blob/main/instructions/reactjs.instructions.md) | ReactJS development standards | ā No | None | Would enhance React development with established patterns |
| [java.instructions.md](https://github.com/github/awesome-copilot/blob/main/instructions/java.instructions.md) | Java development best practices | ā No | None | Could improve Java code quality and consistency |
## Local Instructions Discovery Process
1. List all `*.instructions.md` files in the `instructions/` directory
2. For each discovered file, read front matter to extract `description` and `applyTo` patterns
3. Build comprehensive inventory of existing instructions with their applicable file patterns
4. Use this inventory to avoid suggesting duplicates
## File Structure Requirements
Based on GitHub documentation, copilot-instructions files should be:
- **Repository-wide instructions**: `.github/copilot-instructions.md` (applies to entire repository)
- **Path-specific instructions**: `.github/instructions/NAME.instructions.md` (applies to specific file patterns via `applyTo` frontmatter)
- **Community instructions**: `instructions/NAME.instructions.md` (for sharing and distribution)
## Front Matter Structure
Instructions files in awesome-copilot use this front matter format:
```markdown
---
description: 'Brief description of what this instruction provides'
applyTo: '**/*.js,**/*.ts' # Optional: glob patterns for file matching
---
```
## Requirements
- Use `githubRepo` tool to get content from awesome-copilot repository
- Scan local file system for existing instructions in `instructions/` directory
- Read YAML front matter from local instruction files to extract descriptions and `applyTo` patterns
- Compare against existing instructions in this repository to avoid duplicates
- Focus on gaps in current instruction library coverage
- Validate that suggested instructions align with repository's purpose and standards
- Provide clear rationale for each suggestion
- Include links to both awesome-copilot instructions and similar local instructions
- Consider technology stack compatibility and project-specific needs
- Don't provide any additional information or context beyond the table and the analysis
## Icons Reference
- ā
Already installed in repo
- ā Not installed in repo
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š¦ Package Info
- Format
- copilot
- Type
- prompt
- Category
- ai
- License
- MIT