Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods,

Code Exemplars Blueprint Generator Configuration Variables ${PROJECT TYPE="Auto detect .NET Java JavaScript TypeScript React Angular Python Other"} <! Primary technology ${SCAN DEPTH="Basic Standard Comprehensive"} <! How deeply to analyze the codebase ${INCLUDE CODE SNIPPETS=true false} <! Include actual code snippets in addition to file references ${CATEGORIZATION="Pattern Type Architecture Layer File Type"} <! How to organize exemplars ${MAX EXAMPLES PER CATEGORY=3} <! Maximum number of examples per category ${INCLUDE COMMENTS=true false} <! Include explanatory comments for each exemplar 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: 1. Introduction explaining the purpose of the document 2. Table of contents with links to categories 3. Organized sections based on ${CATEGORIZATION} 4. Up to ${MAX EXAMPLES PER CATEGORY} exemplars per category 5. 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.

code-exemplars-blueprint-generator