sc-design
π―Skillfrom tony363/superclaude
Designs comprehensive system architectures, APIs, and component interfaces using best practices and industry standards.
Installation
npx skills add https://github.com/tony363/superclaude --skill sc-designSkill Details
Design system architecture, APIs, and component interfaces with comprehensive specifications. Use when planning architecture, designing APIs, creating component interfaces, or modeling databases.
Overview
# System & Component Design Skill
Architecture planning and interface design with industry best practices.
Quick Start
```bash
# Architecture design
/sc:design [target] --type architecture
# API specification
/sc:design payment-api --type api --format spec
# Database schema
/sc:design e-commerce --type database --format diagram
```
Behavioral Flow
- Analyze - Examine requirements and existing system context
- Plan - Define design approach based on type and format
- Design - Create specifications with best practices
- Validate - Ensure maintainability and scalability
- Document - Generate diagrams and specifications
Flags
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| --type | string | architecture | architecture, api, component, database |
| --format | string | spec | diagram, spec, code |
Evidence Requirements
This skill does NOT require hard evidence. Deliverables are:
- Design specifications and diagrams
- Interface definitions
- Schema documentation
Design Types
Architecture (`--type architecture`)
- System structure and component relationships
- Scalability and reliability patterns
- Service boundaries and communication
API (`--type api`)
- RESTful/GraphQL endpoint design
- Request/response schemas
- Authentication and versioning
Component (`--type component`)
- Interface contracts and dependencies
- State management patterns
- Integration points
Database (`--type database`)
- Entity relationships and constraints
- Normalization and indexing
- Performance considerations
Output Formats
Diagram (`--format diagram`)
- ASCII or Mermaid diagrams
- Component relationship visualization
- Data flow representation
Specification (`--format spec`)
- OpenAPI/Swagger for APIs
- Detailed interface documentation
- Technical requirements
Code (`--format code`)
- Interface definitions
- Type declarations
- Skeleton implementations
Examples
System Architecture
```
/sc:design user-management --type architecture --format diagram
# Component relationships, data flow, scalability patterns
```
API Design
```
/sc:design payment-api --type api --format spec
# OpenAPI spec with endpoints, schemas, auth patterns
```
Component Interface
```
/sc:design notification-service --type component --format code
# TypeScript/Python interfaces with clear contracts
```
Database Schema
```
/sc:design inventory-db --type database --format diagram
# ER diagrams with relationships and constraints
```
MCP Integration
PAL MCP (Design Validation)
| Tool | When to Use | Purpose |
|------|-------------|---------|
| mcp__pal__planner | Architecture planning | Sequential planning with branching for design decisions |
| mcp__pal__consensus | Design decisions | Multi-model validation of architectural choices |
| mcp__pal__thinkdeep | Complex systems | Deep analysis of system requirements |
| mcp__pal__chat | Brainstorming | Collaborative design exploration |
| mcp__pal__apilookup | API standards | Get current API design best practices |
PAL Usage Patterns
```bash
# Architecture planning
mcp__pal__planner(
step="Designing microservices architecture for e-commerce platform",
step_number=1,
total_steps=4,
more_steps_needed=True
)
# Validate design with consensus
mcp__pal__consensus(
models=[
{"model": "gpt-5.2", "stance": "for"},
{"model": "gemini-3-pro", "stance": "against"},
{"model": "deepseek", "stance": "neutral"}
],
step="Evaluate: Should we use event sourcing for the order management system?"
)
# Deep system analysis
mcp__pal__thinkdeep(
step="Analyzing scalability requirements for real-time notification system",
hypothesis="WebSocket with Redis pub/sub will handle 100k concurrent users",
confidence="medium",
focus_areas=["scalability", "reliability", "performance"]
)
```
Rube MCP (Documentation & Collaboration)
| Tool | When to Use | Purpose |
|------|-------------|---------|
| mcp__rube__RUBE_SEARCH_TOOLS | External tools | Find diagramming, documentation tools |
| mcp__rube__RUBE_MULTI_EXECUTE_TOOL | Share designs | Post to Notion, Confluence, Slack |
| mcp__rube__RUBE_CREATE_UPDATE_RECIPE | Design workflows | Save reusable design processes |
Rube Usage Patterns
```bash
# Create design document in Notion
mcp__rube__RUBE_SEARCH_TOOLS(queries=[
{"use_case": "create notion page", "known_fields": "database:Architecture"}
])
mcp__rube__RUBE_MULTI_EXECUTE_TOOL(tools=[
{"tool_slug": "NOTION_CREATE_PAGE", "arguments": {
"title": "Payment API Design v2",
"content": "## Overview\n..."
}}
])
# Share design for review
mcp__rube__RUBE_MULTI_EXECUTE_TOOL(tools=[
{"tool_slug": "SLACK_SEND_MESSAGE", "arguments": {
"channel": "#architecture",
"text": "New design ready for review: Payment API v2"
}},
{"tool_slug": "JIRA_CREATE_ISSUE", "arguments": {
"project": "ARCH",
"summary": "Review: Payment API Design",
"issue_type": "Task"
}}
])
```
Flags (Extended)
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| --pal-plan | bool | false | Use PAL planner for systematic design |
| --consensus | bool | false | Validate design with multi-model consensus |
| --share | string | - | Share via Rube (notion, confluence, slack) |
| --create-ticket | bool | false | Create review ticket via Rube |
Tool Coordination
- Read - Requirements analysis
- Grep/Glob - Pattern analysis
- Write - Design documentation
- Bash - External tool integration
- PAL MCP - Design planning, consensus validation, deep analysis
- Rube MCP - Documentation sharing, collaboration, review workflows
More from this repository10
Automates data pipeline creation, transformation, and ETL workflows using AI-driven code generation and intelligent data engineering strategies
Automatically updates README.md by analyzing git branch changes with multi-model consensus validation for accurate documentation synchronization.
Performs comprehensive code analysis across quality, security, performance, and architecture domains, generating actionable insights and recommendations.
Generates comprehensive documentation for code components, APIs, and features across various styles and types, providing structured technical documentation with customizable detail levels.
Systematically estimates development tasks by analyzing scope, calculating effort, and providing confidence intervals for time, complexity, and resource planning.
Systematically improve code quality, performance, and maintainability through multi-persona analysis and safe refactoring.
Generates structured implementation workflows by analyzing PRDs and requirements, creating comprehensive, multi-domain development plans with strategic coordination.
Intelligently implements features, APIs, and components by coordinating expertise, applying best practices, and ensuring systematic development.
Automates intelligent git operations with smart commit generation, branch management, and workflow optimization.
Executes comprehensive tests with coverage analysis, real-time tracking, and automated quality reporting across various test types.