{"id":"7add3474-6e66-43ec-9a59-2b346e2cf16e","shortId":"LRyvRb","kind":"skill","title":"Code Exemplars Blueprint Generator","tagline":"Awesome Copilot skill by Github","description":"# Code Exemplars Blueprint Generator\n\n## Configuration Variables\n${PROJECT_TYPE=\"Auto-detect|.NET|Java|JavaScript|TypeScript|React|Angular|Python|Other\"} <!-- Primary technology -->\n${SCAN_DEPTH=\"Basic|Standard|Comprehensive\"} <!-- How deeply to analyze the codebase -->\n${INCLUDE_CODE_SNIPPETS=true|false} <!-- Include actual code snippets in addition to file references -->\n${CATEGORIZATION=\"Pattern Type|Architecture Layer|File Type\"} <!-- How to organize exemplars -->\n${MAX_EXAMPLES_PER_CATEGORY=3} <!-- Maximum number of examples per category -->\n${INCLUDE_COMMENTS=true|false} <!-- Include explanatory comments for each exemplar -->\n\n## Generated Prompt\n\n\"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:\n\n### 1. Codebase Analysis Phase\n- ${PROJECT_TYPE == \"Auto-detect\" ? \"Automatically detect primary programming languages and frameworks by scanning file extensions and configuration files\" : `Focus on ${PROJECT_TYPE} code files`}\n- Identify files with high-quality implementation, good documentation, and clear structure\n- Look for commonly used patterns, architecture components, and well-structured implementations\n- Prioritize files that demonstrate best practices for our technology stack\n- Only reference actual files that exist in the codebase - no hypothetical examples\n\n### 2. Exemplar Identification Criteria\n- Well-structured, readable code with clear naming conventions\n- Comprehensive comments and documentation\n- Proper error handling and validation\n- Adherence to design patterns and architectural principles\n- Separation of concerns and single responsibility principle\n- Efficient implementation without code smells\n- Representative of our standard approaches\n\n### 3. Core Pattern Categories\n\n${PROJECT_TYPE == \".NET\" || PROJECT_TYPE == \"Auto-detect\" ? `#### .NET Exemplars (if detected)\n- **Domain Models**: Find entities that properly implement encapsulation and domain logic\n- **Repository Implementations**: Examples of our data access approach\n- **Service Layer Components**: Well-structured business logic implementations\n- **Controller Patterns**: Clean API controllers with proper validation and responses\n- **Dependency Injection Usage**: Good examples of DI configuration and usage\n- **Middleware Components**: Custom middleware implementations\n- **Unit Test Patterns**: Well-structured tests with proper arrangement and assertions` : \"\"}\n\n${(PROJECT_TYPE == \"JavaScript\" || PROJECT_TYPE == \"TypeScript\" || PROJECT_TYPE == \"React\" || PROJECT_TYPE == \"Angular\" || PROJECT_TYPE == \"Auto-detect\") ? `#### Frontend Exemplars (if detected)\n- **Component Structure**: Clean, well-structured components\n- **State Management**: Good examples of state handling\n- **API Integration**: Well-implemented service calls and data handling\n- **Form Handling**: Validation and submission patterns\n- **Routing Implementation**: Navigation and route configuration\n- **UI Components**: Reusable, well-structured UI elements\n- **Unit Test Examples**: Component and service tests` : \"\"}\n\n${PROJECT_TYPE == \"Java\" || PROJECT_TYPE == \"Auto-detect\" ? `#### Java Exemplars (if detected)\n- **Entity Classes**: Well-designed JPA entities or domain models\n- **Service Implementations**: Clean service layer components\n- **Repository Patterns**: Data access implementations\n- **Controller/Resource Classes**: API endpoint implementations\n- **Configuration Classes**: Application configuration\n- **Unit Tests**: Well-structured JUnit tests` : \"\"}\n\n${PROJECT_TYPE == \"Python\" || PROJECT_TYPE == \"Auto-detect\" ? `#### Python Exemplars (if detected)\n- **Class Definitions**: Well-structured classes with proper documentation\n- **API Routes/Views**: Clean API implementations\n- **Data Models**: ORM model definitions\n- **Service Functions**: Business logic implementations\n- **Utility Modules**: Helper and utility functions\n- **Test Cases**: Well-structured unit tests` : \"\"}\n\n### 4. Architecture Layer Exemplars\n\n- **Presentation Layer**:\n  - User interface components\n  - Controllers/API endpoints\n  - View models/DTOs\n  \n- **Business Logic Layer**:\n  - Service implementations\n  - Business logic components\n  - Workflow orchestration\n  \n- **Data Access Layer**:\n  - Repository implementations\n  - Data models\n  - Query patterns\n  \n- **Cross-Cutting Concerns**:\n  - Logging implementations\n  - Error handling\n  - Authentication/authorization\n  - Validation\n\n### 5. Exemplar Documentation Format\n\nFor each identified exemplar, document:\n- File path (relative to repository root)\n- Brief description of what makes it exemplary\n- Pattern or component type it represents\n${INCLUDE_COMMENTS ? \"- Key implementation details and coding principles demonstrated\" : \"\"}\n${INCLUDE_CODE_SNIPPETS ? \"- Small, representative code snippet (if applicable)\" : \"\"}\n\n${SCAN_DEPTH == \"Comprehensive\" ? `### 6. Additional Documentation\n\n- **Consistency Patterns**: Note consistent patterns observed across the codebase\n- **Architecture Observations**: Document architectural patterns evident in the code\n- **Implementation Conventions**: Identify naming and structural conventions\n- **Anti-patterns to Avoid**: Note any areas where the codebase deviates from best practices` : \"\"}\n\n### ${SCAN_DEPTH == \"Comprehensive\" ? \"7\" : \"6\"}. Output Format\n\nCreate exemplars.md with:\n1. Introduction explaining the purpose of the document\n2. Table of contents with links to categories\n3. Organized sections based on ${CATEGORIZATION}\n4. Up to ${MAX_EXAMPLES_PER_CATEGORY} exemplars per category\n5. Conclusion with recommendations for maintaining code quality\n\nThe document should be actionable for developers needing guidance on implementing new features consistent with existing patterns.\n\nImportant: Only include actual files from the codebase. Verify all file paths exist. Do not include placeholder or hypothetical examples.\n\"\n\n## Expected Output\nUpon 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.","tags":["code","exemplars","blueprint","generator","awesome","copilot","github"],"capabilities":["skill","source-github","category-awesome-copilot"],"categories":["awesome-copilot"],"synonyms":[],"warnings":[],"endpointUrl":"https://skills.sh/github/awesome-copilot/code-exemplars-blueprint-generator","protocol":"skill","transport":"skills-sh","auth":{"type":"none","details":{"install_from":"skills.sh"}},"qualityScore":"0.300","qualityRationale":"deterministic score 0.30 from registry signals: · indexed on skills.sh · published under 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'awesom':5 'base':625 'basic':31 'best':147,594 'blueprint':3,12 'brief':519 'busi':252,446,475,480 'call':333 'case':456 'categor':39,627 'categori':49,214,621,634,637 'category-awesome-copilot' 'class':377,398,403,425,430 'clean':257,315,388,436 'clear':129,175 'code':1,10,35,71,78,117,173,204,538,542,546,573,644,707 'codebas':59,91,161,564,591,670,694 'comment':52,179,533 'common':133 'compon':137,248,276,313,319,350,360,391,470,482,528 'comprehens':33,178,552,598 'concern':196,497 'conclus':639 'configur':14,111,272,348,402,405 'consist':85,556,559,659 'contain':700 'content':617 'control':255,259 'controller/resource':397 'controllers/api':471 'convent':177,575,580 'copilot':6,690 'core':212 'creat':603 'criteria':168 'cross':495 'cross-cut':494 'custom':277 'cut':496 'data':243,335,394,439,485,490 'definit':426,443 'demonstr':76,146,540 'depend':265 'depth':30,551,597 'descript':520 'design':189,380 'detail':536 'detect':20,98,100,222,226,308,312,371,375,420,424 'develop':652 'deviat':592 'di':271 'document':127,181,433,506,512,555,567,613,647 'domain':227,236,384 'effici':201 'element':356 'encapsul':234 'endpoint':400,472 'entiti':230,376,382 'error':183,500 'evid':570 'exampl':47,72,164,240,269,323,359,632,682,708 'exemplar':2,11,74,166,224,310,373,422,465,505,511,635 'exemplari':525 'exemplars.md':63,604,698 'exist':158,661,675 'expect':683 'explain':608 'extens':109 'fals':38,54 'featur':658 'file':44,64,108,112,118,120,144,156,513,667,673,699 'find':229 'focus':113 'follow':88 'form':337 'format':507,602 'framework':105 'frontend':309 'function':445,454 'generat':4,13,55,61,696 'github':9,689 'good':126,268,322 'guidanc':654 'handl':184,326,336,338,501 'help':83 'helper':451 'high':68,123,705 'high-qual':67,122,704 'hypothet':163,681 'identif':167 'identifi':66,119,510,576 'implement':125,142,202,233,239,254,279,331,344,387,396,401,438,448,479,489,499,535,574,656 'import':663 'includ':34,51,532,541,665,678 'inject':266 'integr':328 'interfac':469 'introduct':607 'java':22,366,372 'javascript':23,294 'jpa':381 'junit':411 'key':534 'languag':103 'layer':43,247,390,464,467,477,487 'link':619 'log':498 'logic':237,253,447,476,481 'look':131 'maintain':84,643 'make':523 'manag':321 'max':46,631 'middlewar':275,278 'model':228,385,440,442,491 'models/dtos':474 'modul':450 'name':176,577 'navig':345 'need':653 'net':21,217,223 'new':657 'note':558,586 'observ':561,566 'orchestr':484 'organ':623,712 'orm':441 'output':601,684 'paramet':717 'path':514,674 'pattern':40,81,135,190,213,256,282,342,393,493,526,557,560,569,583,662 'per':48,633,636 'phase':93 'placehold':679 'practic':148,595 'present':466 'primari':101 'principl':193,200,539 'priorit':143 'program':102 'project':16,94,115,215,218,292,295,298,301,304,364,367,413,416 'prompt':56,688 'proper':182,232,261,288,432 'purpos':610 'python':27,415,421 'qualiti':69,124,645,706 'queri':492 'react':25,300 'readabl':172 'real':701 'recommend':641 'refer':154,702 'relat':515 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