12 KiB
name, description
| name | description |
|---|---|
| architecture-design | Generate comprehensive software architecture documentation (ARCHITECTURE.md) with C4 diagrams, OpenAPI specs, and technology-specific guidance. This skill should be used when creating architecture documentation for new projects, documenting existing systems, or updating architectural specifications. |
Architecture Design
Generate professional software architecture documentation with visual diagrams and API specifications through structured interviews. Create complete ARCHITECTURE.md files covering all required sections with technology-specific patterns, C4 model diagrams, and OpenAPI 3.0 specifications.
Core Workflow
Step 1: Assess Project Type
Determine the project type by asking the user:
- New project? Gather requirements and design architecture
- Existing system? Document current state
- Update needed? Identify changed components
Step 2: Gather Essential Information
Conduct a brief interview (5-7 questions maximum) to collect:
- Architecture pattern: Monolith, microservices, or serverless?
- Primary technology: Node.js, Python, Java, or other?
- Key components: Main services or modules?
- Data stores: Databases and caches?
- Cloud provider: AWS, GCP, Azure, or on-premise?
- Deployment: How is it deployed?
- External integrations: Third-party services?
Step 3: Select Template and Load References
Choose template based on architecture pattern:
- Monolith → Use
assets/ARCHITECTURE-monolith.md - Microservices → Use
assets/ARCHITECTURE-microservices.md - Uncertain → Use
assets/ARCHITECTURE.md
Load technology-specific references:
- Node.js projects → Load
references/nodejs.mdfor Express, NestJS, Fastify patterns - Python projects → Load
references/python.mdfor Django, Flask, FastAPI patterns - Java projects → Load
references/java.mdfor Spring Boot, Jakarta EE patterns
Load pattern-specific references when applicable:
- Microservices → Load
references/microservices.mdfor service boundaries and communication patterns - Serverless → Load
references/serverless.mdfor function organization and event sources
Step 4: Generate System Diagram
Generate appropriate diagrams using scripts/generate_diagram.py:
For monolithic architectures:
python scripts/generate_diagram.py layered
For microservices architectures:
python scripts/generate_diagram.py flow
For simple systems:
python scripts/generate_diagram.py simple
Customize diagrams with JSON configuration for specific components.
Step 5: Populate Template
Complete the template sections in the specified order:
- Project Identification (Section 10) - Add project name, repository, contact, date
- Project Structure (Section 1) - Define directory layout
- System Diagram (Section 2) - Insert generated diagram
- Core Components (Section 3) - Document components from interview
- Data Stores (Section 4) - Describe databases and caches
- External Integrations (Section 5) - List third-party services
- Deployment (Section 6) - Detail infrastructure setup
- Security (Section 7) - Specify authentication and encryption
- Development (Section 8) - Outline setup and testing procedures
- Future Considerations (Section 9) - Document roadmap items
- Glossary (Section 11) - Define domain terminology
Apply technology-specific patterns from loaded references to enhance each section.
Step 6: Validate
Execute the validation script to ensure quality:
python scripts/validate_architecture.py ARCHITECTURE.md
Address any issues or warnings before delivering the documentation.
Interview Best Practices
Maintain focused questioning:
- Ask 2-3 questions at a time
- Build upon previous answers
- Skip redundant questions
Adapt communication style:
- Technical users: Use precise terminology
- Non-technical users: Simplify language
- Uncertain users: Offer defaults or placeholders
Handle information gaps:
- Mark uncertain items for review
- Add [TODO] for missing information
- Suggest reasonable defaults based on context
Technology-Specific Guidance
Reference Loading Guidelines
Load references/nodejs.md for:
- Express, NestJS, Fastify projects
- Node.js microservices
- Serverless Node functions
Load references/python.md for:
- Django, Flask, FastAPI projects
- Python microservices
- Data pipelines and ML systems
Load references/java.md for:
- Spring Boot applications
- Jakarta EE systems
- Java microservices
Load references/workflows.md for:
- Complex interview scenarios
- Detailed process guidance
- Documentation update workflows
Applying Technology Patterns
After loading references, apply the patterns to enhance:
- Project structure recommendations
- Deployment configurations
- Framework-specific best practices
- Common library suggestions
- Testing strategies and approaches
Pattern-Specific Guidance
Microservices Architecture
Load references/microservices.md and include these elements:
- Service boundaries and responsibilities
- Communication patterns (synchronous vs asynchronous)
- API gateway configuration
- Service discovery mechanism
- Data management approach
- Observability and monitoring setup
Use the microservices template (assets/ARCHITECTURE-microservices.md) for proper structure.
Serverless Architecture
Load references/serverless.md and include these elements:
- Function organization and boundaries
- Event sources and triggers
- State management approach
- Cold start mitigation techniques
- Cost optimization strategies
Monolithic Architecture
Use the monolith template (assets/ARCHITECTURE-monolith.md) and emphasize:
- Layered architecture patterns
- Module organization principles
- Potential future refactoring paths
- Scaling strategy and approaches
Diagram Generation Examples
Simple Architecture Diagram
python scripts/generate_diagram.py simple '{"components": ["User", "API", "DB"], "connections": [["User", "API"], ["API", "DB"]]}'
Layered Architecture Diagram
python scripts/generate_diagram.py layered '{"Presentation": ["Web UI"], "Business": ["API"], "Data": ["PostgreSQL"]}'
Flow Architecture Diagram
python scripts/generate_diagram.py flow '[{"from": "Client", "to": "Gateway", "label": "HTTP"}, {"from": "Gateway", "to": "Service", "label": "route"}]'
C4 Context Diagram
python scripts/generate_diagram.py c4 '{"system": "E-commerce Platform", "actors": ["Customer", "Admin"], "external_systems": ["Payment Gateway", "Email Service"]}'
Integrate generated diagrams into Section 2 (System Diagram) of the ARCHITECTURE.md template.
Validation
Execute validation before delivering documentation:
python scripts/validate_architecture.py ARCHITECTURE.md
Validation checks performed:
- Verify all 11 sections are present
- Confirm required fields in Project Identification section
- Ensure minimal content in each section
- Count and report placeholder usage
Address any warnings about missing content or excessive placeholders.
Documentation Update Workflow
For incremental updates:
- Identify what has changed
- Update only affected sections
- Update the date in Section 10 (Project Identification)
- Re-run validation to ensure quality
For major updates:
- Review the entire document
- Regenerate diagrams if structure has changed
- Update multiple sections as needed
- Consider adding version notes
Mermaid Diagram Generation
After creating ARCHITECTURE.md, generate the complete set of 5 Mermaid diagrams.
Load Mermaid Instructions
When users request diagrams or complete documentation packages:
Load references/mermaid-diagrams.md
Generate Complete Diagram Set
Create all 5 diagrams following the guidance in mermaid-diagrams.md:
- C4 Context (Level 1) - System in its broader context
- C4 Container (Level 2) - Main application containers
- C4 Component (Level 3) - Internal component structure
- Data Flow - How data moves through the system
- C4 Deployment - Infrastructure topology and deployment
Use scripts/generate_mermaid.py with system JSON configuration.
Save diagrams as separate .mmd files:
01-context.mmd02-container.mmd03-component.mmd04-dataflow.mmd05-deployment.mmd
Embed diagrams in ARCHITECTURE.md Section 2 as code blocks for easy viewing and editing.
OpenAPI Specification Generation
For systems with REST APIs, generate comprehensive OpenAPI 3.0 specifications.
Generate API Specifications
Use scripts/generate_openapi.py with appropriate parameters:
For simple CRUD operations:
python scripts/generate_openapi.py "ResourceName"
For custom API specifications:
python scripts/generate_openapi.py '{"system_name": "...", "endpoints": [...]}'
Save the generated specification as openapi.json in the project directory.
Complete Documentation Workflow
Follow this end-to-end workflow for comprehensive architecture documentation:
- Conduct structured interview (5-7 questions maximum)
- Select appropriate template and load relevant references
- Setup work directory: Use current working directory
$(pwd) - Generate ARCHITECTURE.md with all 11 sections completed
- Generate Mermaid diagrams (5 separate .mmd files) in work directory root
- Generate OpenAPI specification (if applicable) in work directory
- Deliver all generated artifacts to the user
Deliverable Organization
Organize generated documentation files as follows:
├── ARCHITECTURE.md # Main architecture document
├── openapi.json # API specification (if applicable)
├── *.mmd (5 files) # Mermaid diagram sources
│ ├── 01-context.mmd
│ ├── 02-container.mmd
│ ├── 03-component.mmd
│ ├── 04-dataflow.mmd
│ └── 05-deployment.mmd
└── diagrams/ (created during packaging)
└── *.png (5 files, if rendered to images)
Example Usage
User request: "Create architecture documentation for my Node.js microservices project"
Execution approach:
- Select microservices template (
assets/ARCHITECTURE-microservices.md) - Load
references/nodejs.mdandreferences/microservices.md - Conduct focused interview: services, databases, communication patterns, deployment
- Generate flow diagram using
scripts/generate_diagram.py flow - Populate all sections with Node.js and microservices-specific patterns
- Validate using
scripts/validate_architecture.py - Create comprehensive ARCHITECTURE.md in work directory
Common Usage Scenarios
New Greenfield Projects
- Use base template (
assets/ARCHITECTURE.md) - Focus on design decisions and architecture rationale
- Include justification for technology choices
- Emphasize planned architecture and future scalability
Existing System Documentation
- Ask about current pain points and challenges
- Document the as-is state accurately
- Note planned improvements in Section 9 (Future Considerations)
- Capture current technology stack and limitations
Legacy System Analysis
- Identify undocumented or poorly understood areas
- Mark uncertain items for further investigation
- Suggest areas requiring clarification from stakeholders
- Document assumptions and risks
Architecture Reviews and Updates
- Update only sections that have changed
- Preserve information that remains accurate
- Add new components and relationships
- Update date in Section 10 and note changes
Best Practices
Efficient documentation creation:
- Begin with known information and build incrementally
- Use placeholders for unknown items to maintain momentum
- Leverage technology references to save time and ensure accuracy
- Validate frequently to catch issues early
High-quality output standards:
- Provide specific, concrete details rather than generic descriptions
- Include actual technology stack versions and configurations
- Use real service names, purposes, and data flows
- Document concrete deployment infrastructure and environments
Positive user experience:
- Avoid overwhelming users with excessive questions
- Explain the documentation process and next steps
- Show progress through the 11 sections clearly
- Offer refinement and improvement after initial delivery