@awesome-copilot/copilot-suggest-awesome-github-copilot-collections
Suggest relevant GitHub Copilot collections from the awesome-copilot repository based on current repository context and chat history, providing automatic download and installation of collection assets.
prpm install @awesome-copilot/copilot-suggest-awesome-github-copilot-collections0 total downloads
š Full Prompt Content
---
mode: 'agent'
description: 'Suggest relevant GitHub Copilot collections from the awesome-copilot repository based on current repository context and chat history, providing automatic download and installation of collection assets.'
tools: ['edit', 'search', 'runCommands', 'runTasks', 'think', 'changes', 'testFailure', 'openSimpleBrowser', 'fetch', 'githubRepo', 'todos', 'search']
---
# Suggest Awesome GitHub Copilot Collections
Analyze current repository context and suggest relevant collections from the [GitHub awesome-copilot repository](https://github.com/github/awesome-copilot/blob/main/README.collections.md) that would enhance the development workflow for this repository.
## Process
1. **Fetch Available Collections**: Extract collection list and descriptions from [awesome-copilot README.collections.md](https://github.com/github/awesome-copilot/blob/main/README.collections.md). Must use `#fetch` tool.
2. **Scan Local Assets**: Discover existing prompt files in `prompts/`, instruction files in `instructions/`, and chat modes in `chatmodes/` folders
3. **Extract Local Descriptions**: Read front matter from local asset files to understand existing capabilities
4. **Analyze Repository Context**: Review chat history, repository files, programming languages, frameworks, and current project needs
5. **Match Collection Relevance**: Compare available collections against identified patterns and requirements
6. **Check Asset Overlap**: For relevant collections, analyze individual items to avoid duplicates with existing repository assets
7. **Present Collection Options**: Display relevant collections with descriptions, item counts, and rationale for suggestion
8. **Provide Usage Guidance**: Explain how the installed collection enhances the development workflow
**AWAIT** user request to proceed with installation of specific collections. DO NOT INSTALL UNLESS DIRECTED TO DO SO.
9. **Download Assets**: For requested collections, automatically download and install each individual asset (prompts, instructions, chat modes) to appropriate directories. Do NOT adjust content of the files. 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, .bicep, .tf, etc.)
- Framework indicators (ASP.NET, React, Azure, Next.js, Angular, etc.)
- Project types (web apps, APIs, libraries, tools, infrastructure)
- Documentation needs (README, specs, ADRs, architectural decisions)
- Development workflow indicators (CI/CD, testing, deployment)
šØļø **Chat History Context**:
- Recent discussions and pain points
- Feature requests or implementation needs
- Code review patterns and quality concerns
- Development workflow requirements and challenges
- Technology stack and architecture decisions
## Output Format
Display analysis results in structured table showing relevant collections and their potential value:
### Collection Recommendations
| Collection Name | Description | Items | Asset Overlap | Suggestion Rationale |
|-----------------|-------------|-------|---------------|---------------------|
| [Azure & Cloud Development](https://github.com/github/awesome-copilot/blob/main/collections/azure-cloud-development.md) | Comprehensive Azure cloud development tools including Infrastructure as Code, serverless functions, architecture patterns, and cost optimization | 15 items | 3 similar | Would enhance Azure development workflow with Bicep, Terraform, and cost optimization tools |
| [C# .NET Development](https://github.com/github/awesome-copilot/blob/main/collections/csharp-dotnet-development.md) | Essential prompts, instructions, and chat modes for C# and .NET development including testing, documentation, and best practices | 7 items | 2 similar | Already covered by existing .NET-related assets but includes advanced testing patterns |
| [Testing & Test Automation](https://github.com/github/awesome-copilot/blob/main/collections/testing-automation.md) | Comprehensive collection for writing tests, test automation, and test-driven development | 11 items | 1 similar | Could significantly improve testing practices with TDD guidance and automation tools |
### Asset Analysis for Recommended Collections
For each suggested collection, break down individual assets:
**Azure & Cloud Development Collection Analysis:**
- ā
**New Assets (12)**: Azure cost optimization prompts, Bicep planning mode, AVM modules, Logic Apps expert mode
- ā ļø **Similar Assets (3)**: Azure DevOps pipelines (similar to existing CI/CD), Terraform (basic overlap), Containerization (Docker basics covered)
- šÆ **High Value**: Cost optimization tools, Infrastructure as Code expertise, Azure-specific architectural guidance
**Installation Preview:**
- Will install to `prompts/`: 4 Azure-specific prompts
- Will install to `instructions/`: 6 infrastructure and DevOps best practices
- Will install to `chatmodes/`: 5 specialized Azure expert modes
## Local Asset Discovery Process
1. **Scan Asset Directories**:
- List all `*.prompt.md` files in `prompts/` directory
- List all `*.instructions.md` files in `instructions/` directory
- List all `*.chatmode.md` files in `chatmodes/` directory
2. **Extract Asset Metadata**: For each discovered file, read YAML front matter to extract:
- `description` - Primary purpose and functionality
- `tools` - Required tools and capabilities
- `mode` - Operating mode (for prompts)
- `model` - Specific model requirements (for chat modes)
3. **Build Asset Inventory**: Create comprehensive map of existing capabilities organized by:
- **Technology Focus**: Programming languages, frameworks, platforms
- **Workflow Type**: Development, testing, deployment, documentation, planning
- **Specialization Level**: General purpose vs. specialized expert modes
4. **Identify Coverage Gaps**: Compare existing assets against:
- Repository technology stack requirements
- Development workflow needs indicated by chat history
- Industry best practices for identified project types
- Missing expertise areas (security, performance, architecture, etc.)
## Collection Asset Download Process
When user confirms a collection installation:
1. **Fetch Collection Manifest**: Get collection YAML from awesome-copilot repository
2. **Download Individual Assets**: For each item in collection:
- Download raw file content from GitHub
- Validate file format and front matter structure
- Check naming convention compliance
3. **Install to Appropriate Directories**:
- `*.prompt.md` files ā `prompts/` directory
- `*.instructions.md` files ā `instructions/` directory
- `*.chatmode.md` files ā `chatmodes/` directory
4. **Avoid Duplicates**: Skip files that are substantially similar to existing assets
5. **Report Installation**: Provide summary of installed assets and usage instructions
## Requirements
- Use `fetch` tool to get collections data from awesome-copilot repository
- Use `githubRepo` tool to get individual asset content for download
- Scan local file system for existing assets in `prompts/`, `instructions/`, and `chatmodes/` directories
- Read YAML front matter from local asset files to extract descriptions and capabilities
- Compare collections against repository context to identify relevant matches
- Focus on collections that fill capability gaps rather than duplicate existing assets
- Validate that suggested collections align with repository's technology stack and development needs
- Provide clear rationale for each collection suggestion with specific benefits
- Enable automatic download and installation of collection assets to appropriate directories
- Ensure downloaded assets follow repository naming conventions and formatting standards
- Provide usage guidance explaining how collections enhance the development workflow
- Include links to both awesome-copilot collections and individual assets within collections
## Collection Installation Workflow
1. **User Confirms Collection**: User selects specific collection(s) for installation
2. **Fetch Collection Manifest**: Download YAML manifest from awesome-copilot repository
3. **Asset Download Loop**: For each asset in collection:
- Download raw content from GitHub repository
- Validate file format and structure
- Check for substantial overlap with existing local assets
- Install to appropriate directory (`prompts/`, `instructions/`, or `chatmodes/`)
4. **Installation Summary**: Report installed assets with usage instructions
5. **Workflow Enhancement Guide**: Explain how the collection improves development capabilities
## Post-Installation Guidance
After installing a collection, provide:
- **Asset Overview**: List of installed prompts, instructions, and chat modes
- **Usage Examples**: How to activate and use each type of asset
- **Workflow Integration**: Best practices for incorporating assets into development process
- **Customization Tips**: How to modify assets for specific project needs
- **Related Collections**: Suggestions for complementary collections that work well together
## Icons Reference
- ā
Collection recommended for installation
- ā ļø Collection has some asset overlap but still valuable
- ā Collection not recommended (significant overlap or not relevant)
- šÆ High-value collection that fills major capability gaps
- š Collection partially installed (some assets skipped due to duplicates)
- š Collection needs customization for repository-specific needs
š” Suggested Test Inputs
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šÆ Community Test Results
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š¦ Package Info
- Format
- copilot
- Type
- prompt
- Category
- ai
- License
- MIT