code-exemplars-blueprint-generator

安装量: 7.1K
排名: #469

安装

npx skills add https://github.com/github/awesome-copilot --skill code-exemplars-blueprint-generator
Code Exemplars Blueprint Generator
Configuration Variables
${PROJECT_TYPE="Auto-detect|.NET|Java|JavaScript|TypeScript|React|Angular|Python|Other"}
${SCAN_DEPTH="Basic|Standard|Comprehensive"}
${INCLUDE_CODE_SNIPPETS=true|false}
${CATEGORIZATION="Pattern Type|Architecture Layer|File Type"}
${MAX_EXAMPLES_PER_CATEGORY=3}
${INCLUDE_COMMENTS=true|false}
Generated Prompt
"Scan this codebase and generate an exemplars.md file that identifies high-quality, representative code examples. The exemplars should demonstrate our coding standards and patterns to help maintain consistency. Use the following approach:
1. Codebase Analysis Phase
${PROJECT_TYPE == "Auto-detect" ? "Automatically detect primary programming languages and frameworks by scanning file extensions and configuration files" :
Focus on ${PROJECT_TYPE} code files
}
Identify files with high-quality implementation, good documentation, and clear structure
Look for commonly used patterns, architecture components, and well-structured implementations
Prioritize files that demonstrate best practices for our technology stack
Only reference actual files that exist in the codebase - no hypothetical examples
2. Exemplar Identification Criteria
Well-structured, readable code with clear naming conventions
Comprehensive comments and documentation
Proper error handling and validation
Adherence to design patterns and architectural principles
Separation of concerns and single responsibility principle
Efficient implementation without code smells
Representative of our standard approaches
3. Core Pattern Categories
${PROJECT_TYPE == ".NET" || PROJECT_TYPE == "Auto-detect" ? `#### .NET Exemplars (if detected)
Domain Models
Find entities that properly implement encapsulation and domain logic
Repository Implementations
Examples of our data access approach
Service Layer Components
Well-structured business logic implementations
Controller Patterns
Clean API controllers with proper validation and responses
Dependency Injection Usage
Good examples of DI configuration and usage
Middleware Components
Custom middleware implementations
Unit Test Patterns
Well-structured tests with proper arrangement and assertions` : ""}
${(PROJECT_TYPE == "JavaScript" || PROJECT_TYPE == "TypeScript" || PROJECT_TYPE == "React" || PROJECT_TYPE == "Angular" || PROJECT_TYPE == "Auto-detect") ? `#### Frontend Exemplars (if detected)
Component Structure
Clean, well-structured components
State Management
Good examples of state handling
API Integration
Well-implemented service calls and data handling
Form Handling
Validation and submission patterns
Routing Implementation
Navigation and route configuration
UI Components
Reusable, well-structured UI elements
Unit Test Examples
Component and service tests` : ""}
${PROJECT_TYPE == "Java" || PROJECT_TYPE == "Auto-detect" ? `#### Java Exemplars (if detected)
Entity Classes
Well-designed JPA entities or domain models
Service Implementations
Clean service layer components
Repository Patterns
Data access implementations
Controller/Resource Classes
API endpoint implementations
Configuration Classes
Application configuration
Unit Tests
Well-structured JUnit tests` : ""}
${PROJECT_TYPE == "Python" || PROJECT_TYPE == "Auto-detect" ? `#### Python Exemplars (if detected)
Class Definitions
Well-structured classes with proper documentation
API Routes/Views
Clean API implementations
Data Models
ORM model definitions
Service Functions
Business logic implementations
Utility Modules
Helper and utility functions
Test Cases
Well-structured unit tests` : ""}
4. Architecture Layer Exemplars
Presentation Layer
:
User interface components
Controllers/API endpoints
View models/DTOs
Business Logic Layer
:
Service implementations
Business logic components
Workflow orchestration
Data Access Layer
:
Repository implementations
Data models
Query patterns
Cross-Cutting Concerns
:
Logging implementations
Error handling
Authentication/authorization
Validation
5. Exemplar Documentation Format
For each identified exemplar, document:
File path (relative to repository root)
Brief description of what makes it exemplary
Pattern or component type it represents
${INCLUDE_COMMENTS ? "- Key implementation details and coding principles demonstrated" : ""}
${INCLUDE_CODE_SNIPPETS ? "- Small, representative code snippet (if applicable)" : ""}
${SCAN_DEPTH == "Comprehensive" ? `### 6. Additional Documentation
Consistency Patterns
Note consistent patterns observed across the codebase
Architecture Observations
Document architectural patterns evident in the code
Implementation Conventions
Identify naming and structural conventions
Anti-patterns to Avoid
Note any areas where the codebase deviates from best practices` : ""} ${SCAN_DEPTH == "Comprehensive" ? "7" : "6"}. Output Format Create exemplars.md with: Introduction explaining the purpose of the document Table of contents with links to categories Organized sections based on ${CATEGORIZATION} Up to ${MAX_EXAMPLES_PER_CATEGORY} exemplars per category Conclusion with recommendations for maintaining code quality The document should be actionable for developers needing guidance on implementing new features consistent with existing patterns. Important: Only include actual files from the codebase. Verify all file paths exist. Do not include placeholder or hypothetical examples. " Expected Output Upon running this prompt, GitHub Copilot will scan your codebase and generate an exemplars.md file containing real references to high-quality code examples in your repository, organized according to your selected parameters.
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