code-exemplars-blueprint-generator

Name: code-exemplars-blueprint-generator
Author: github

8.7kinstalls4.6kforks

How to install code-exemplars-blueprint-generator?

github/awesome-copilot/code-exemplars-blueprint-generator

$npx -y skills add github/awesome-copilot --skill code-exemplars-blueprint-generator

Installs into the current project.

Summary

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, cat

Files · 1

View on GitHub

SKILL.md

1	# Code Exemplars Blueprint Generator
2
3	## Configuration Variables
4	${PROJECT_TYPE="Auto-detect\|.NET\|Java\|JavaScript\|TypeScript\|React\|Angular\|Python\|Other"} <!-- Primary technology -->
5	${SCAN_DEPTH="Basic\|Standard\|Comprehensive"} <!-- How deeply to analyze the codebase -->
6	${INCLUDE_CODE_SNIPPETS=true\|false} <!-- Include actual code snippets in addition to file references -->
7	${CATEGORIZATION="Pattern Type\|Architecture Layer\|File Type"} <!-- How to organize exemplars -->
8	${MAX_EXAMPLES_PER_CATEGORY=3} <!-- Maximum number of examples per category -->
9	${INCLUDE_COMMENTS=true\|false} <!-- Include explanatory comments for each exemplar -->
10
11	## Generated Prompt
12
13	"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:
14
15	### 1. Codebase Analysis Phase
16	- ${PROJECT_TYPE == "Auto-detect" ? "Automatically detect primary programming languages and frameworks by scanning file extensions and configuration files" : `Focus on ${PROJECT_TYPE} code files`}
17	- Identify files with high-quality implementation, good documentation, and clear structure
18	- Look for commonly used patterns, architecture components, and well-structured implementations
19	- Prioritize files that demonstrate best practices for our technology stack
20	- Only reference actual files that exist in the codebase - no hypothetical examples
21
22	### 2. Exemplar Identification Criteria
23	- Well-structured, readable code with clear naming conventions
24	- Comprehensive comments and documentation
25	- Proper error handling and validation
26	- Adherence to design patterns and architectural principles
27	- Separation of concerns and single responsibility principle
28	- Efficient implementation without code smells
29	- Representative of our standard approaches
30
31	### 3. Core Pattern Categories
32
33	${PROJECT_TYPE == ".NET" \|\| PROJECT_TYPE == "Auto-detect" ? `#### .NET Exemplars (if detected)
34	- Domain Models: Find entities that properly implement encapsulation and domain logic
35	- Repository Implementations: Examples of our data access approach
36	- Service Layer Components: Well-structured business logic implementations
37	- Controller Patterns: Clean API controllers with proper validation and responses
38	- Dependency Injection Usage: Good examples of DI configuration and usage
39	- Middleware Components: Custom middleware implementations
40	- Unit Test Patterns: Well-structured tests with proper arrangement and assertions` : ""}
41
42	${(PROJECT_TYPE == "JavaScript" \|\| PROJECT_TYPE == "TypeScript" \|\| PROJECT_TYPE == "React" \|\| PROJECT_TYPE == "Angular" \|\| PROJECT_TYPE == "Auto-detect") ? `#### Frontend Exemplars (if detected)
43	- Component Structure: Clean, well-structured components
44	- State Management: Good examples of state handling
45	- API Integration: Well-implemented service calls and data handling
46	- Form Handling: Validation and submission patterns
47	- Routing Implementation: Navigation and route configuration
48	- UI Components: Reusable, well-structured UI elements
49	- Unit Test Examples: Component and service tests` : ""}
50
51	${PROJECT_TYPE == "Java" \|\| PROJECT_TYPE == "Auto-detect" ? `#### Java Exemplars (if detected)
52	- Entity Classes: Well-designed JPA entities or domain models
53	- Service Implementations: Clean service layer components
54	- Repository Patterns: Data access implementations
55	- Controller/Resource Classes: API endpoint implementations
56	- Configuration Classes: Application configuration
57	- Unit Tests: Well-structured JUnit tests` : ""}
58
59	${PROJECT_TYPE == "Python" \|\| PROJECT_TYPE == "Auto-detect" ? `#### Python Exemplars (if detected)
60	- Class Definitions: Well-structured classes with proper documentation
61	- API Routes/Views: Clean API implementations
62	- Data Models: ORM model definitions
63	- Service Functions: Business logic implementations
64	- Utility Modules: Helper and utility functions
65	- Test Cases: Well-structured unit tests` : ""}
66
67	### 4. Architecture Layer Exemplars
68
69	- Presentation Layer:
70	- User interface components
71	- Controllers/API endpoints
72	- View models/DTOs
73
74	- Business Logic Layer:
75	- Service implementations
76	- Business logic components
77	- Workflow orchestration
78
79	- Data Access Layer:
80	- Repository implementations
81	- Data models
82	- Query patterns
83
84	- Cross-Cutting Concerns:
85	- Logging implementations
86	- Error handling
87	- Authentication/author

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Type

code-exemplars-blueprint-generator

8.7kinstalls4.6kforks

View on GitHub

How to install code-exemplars-blueprint-generator?

github/awesome-copilot/code-exemplars-blueprint-generator

$npx -y skills add github/awesome-copilot --skill code-exemplars-blueprint-generator

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Code Exemplars Blueprint Generator
2
3	## Configuration Variables
4	${PROJECT_TYPE="Auto-detect\|.NET\|Java\|JavaScript\|TypeScript\|React\|Angular\|Python\|Other"} <!-- Primary technology -->
5	${SCAN_DEPTH="Basic\|Standard\|Comprehensive"} <!-- How deeply to analyze the codebase -->
6	${INCLUDE_CODE_SNIPPETS=true\|false} <!-- Include actual code snippets in addition to file references -->
7	${CATEGORIZATION="Pattern Type\|Architecture Layer\|File Type"} <!-- How to organize exemplars -->
8	${MAX_EXAMPLES_PER_CATEGORY=3} <!-- Maximum number of examples per category -->
9	${INCLUDE_COMMENTS=true\|false} <!-- Include explanatory comments for each exemplar -->
10
11	## Generated Prompt
12
13	"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:
14
15	### 1. Codebase Analysis Phase
16	- ${PROJECT_TYPE == "Auto-detect" ? "Automatically detect primary programming languages and frameworks by scanning file extensions and configuration files" : `Focus on ${PROJECT_TYPE} code files`}
17	- Identify files with high-quality implementation, good documentation, and clear structure
18	- Look for commonly used patterns, architecture components, and well-structured implementations
19	- Prioritize files that demonstrate best practices for our technology stack
20	- Only reference actual files that exist in the codebase - no hypothetical examples
21
22	### 2. Exemplar Identification Criteria
23	- Well-structured, readable code with clear naming conventions
24	- Comprehensive comments and documentation
25	- Proper error handling and validation
26	- Adherence to design patterns and architectural principles
27	- Separation of concerns and single responsibility principle
28	- Efficient implementation without code smells
29	- Representative of our standard approaches
30
31	### 3. Core Pattern Categories
32
33	${PROJECT_TYPE == ".NET" \|\| PROJECT_TYPE == "Auto-detect" ? `#### .NET Exemplars (if detected)
34	- Domain Models: Find entities that properly implement encapsulation and domain logic
35	- Repository Implementations: Examples of our data access approach
36	- Service Layer Components: Well-structured business logic implementations
37	- Controller Patterns: Clean API controllers with proper validation and responses
38	- Dependency Injection Usage: Good examples of DI configuration and usage
39	- Middleware Components: Custom middleware implementations
40	- Unit Test Patterns: Well-structured tests with proper arrangement and assertions` : ""}
41
42	${(PROJECT_TYPE == "JavaScript" \|\| PROJECT_TYPE == "TypeScript" \|\| PROJECT_TYPE == "React" \|\| PROJECT_TYPE == "Angular" \|\| PROJECT_TYPE == "Auto-detect") ? `#### Frontend Exemplars (if detected)
43	- Component Structure: Clean, well-structured components
44	- State Management: Good examples of state handling
45	- API Integration: Well-implemented service calls and data handling
46	- Form Handling: Validation and submission patterns
47	- Routing Implementation: Navigation and route configuration
48	- UI Components: Reusable, well-structured UI elements
49	- Unit Test Examples: Component and service tests` : ""}
50
51	${PROJECT_TYPE == "Java" \|\| PROJECT_TYPE == "Auto-detect" ? `#### Java Exemplars (if detected)
52	- Entity Classes: Well-designed JPA entities or domain models
53	- Service Implementations: Clean service layer components
54	- Repository Patterns: Data access implementations
55	- Controller/Resource Classes: API endpoint implementations
56	- Configuration Classes: Application configuration
57	- Unit Tests: Well-structured JUnit tests` : ""}
58
59	${PROJECT_TYPE == "Python" \|\| PROJECT_TYPE == "Auto-detect" ? `#### Python Exemplars (if detected)
60	- Class Definitions: Well-structured classes with proper documentation
61	- API Routes/Views: Clean API implementations
62	- Data Models: ORM model definitions
63	- Service Functions: Business logic implementations
64	- Utility Modules: Helper and utility functions
65	- Test Cases: Well-structured unit tests` : ""}
66
67	### 4. Architecture Layer Exemplars
68
69	- Presentation Layer:
70	- User interface components
71	- Controllers/API endpoints
72	- View models/DTOs
73
74	- Business Logic Layer:
75	- Service implementations
76	- Business logic components
77	- Workflow orchestration
78
79	- Data Access Layer:
80	- Repository implementations
81	- Data models
82	- Query patterns
83
84	- Cross-Cutting Concerns:
85	- Logging implementations
86	- Error handling
87	- Authentication/author

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Type