SuperClaude/docs/Reference/basic-examples.md
kazuki nakai 050d5ea2ab
refactor: PEP8 compliance - directory rename and code formatting (#425)
* fix(orchestration): add WebFetch auto-trigger for infrastructure configuration

Problem: Infrastructure configuration changes (e.g., Traefik port settings)
were being made based on assumptions without consulting official documentation,
violating the 'Evidence > assumptions' principle in PRINCIPLES.md.

Solution:
- Added Infrastructure Configuration Validation section to MODE_Orchestration.md
- Auto-triggers WebFetch for infrastructure tools (Traefik, nginx, Docker, etc.)
- Enforces MODE_DeepResearch activation for investigation
- BLOCKS assumption-based configuration changes

Testing: Verified WebFetch successfully retrieves Traefik official docs (port 80 default)

This prevents production outages from infrastructure misconfiguration by ensuring
all technical recommendations are backed by official documentation.

* feat: Add PM Agent (Project Manager Agent) for seamless orchestration

Introduces PM Agent as the default orchestration layer that coordinates
all sub-agents and manages workflows automatically.

Key Features:
- Default orchestration: All user interactions handled by PM Agent
- Auto-delegation: Intelligent sub-agent selection based on task analysis
- Docker Gateway integration: Zero-token baseline with dynamic MCP loading
- Self-improvement loop: Automatic documentation of patterns and mistakes
- Optional override: Users can specify sub-agents explicitly if desired

Architecture:
- Agent spec: SuperClaude/Agents/pm-agent.md
- Command: SuperClaude/Commands/pm.md
- Updated docs: README.md (15→16 agents), agents.md (new Orchestration category)

User Experience:
- Default: PM Agent handles everything (seamless, no manual routing)
- Optional: Explicit --agent flag for direct sub-agent access
- Both modes available simultaneously (no user downside)

Implementation Status:
-  Specification complete
-  Documentation complete
-  Prototype implementation needed
-  Docker Gateway integration needed
-  Testing and validation needed

Refs: kazukinakai/docker-mcp-gateway (IRIS MCP Gateway integration)

* feat: Add Agent Orchestration rules for PM Agent default activation

Implements PM Agent as the default orchestration layer in RULES.md.

Key Changes:
- New 'Agent Orchestration' section (CRITICAL priority)
- PM Agent receives ALL user requests by default
- Manual override with @agent-[name] bypasses PM Agent
- Agent Selection Priority clearly defined:
  1. Manual override → Direct routing
  2. Default → PM Agent → Auto-delegation
  3. Delegation based on keywords, file types, complexity, context

User Experience:
- Default: PM Agent handles everything (seamless)
- Override: @agent-[name] for direct specialist access
- Transparent: PM Agent reports delegation decisions

This establishes PM Agent as the orchestration layer while
respecting existing auto-activation patterns and manual overrides.

Next Steps:
- Local testing in agiletec project
- Iteration based on actual behavior
- Documentation updates as needed

* refactor(pm-agent): redesign as self-improvement meta-layer

Problem Resolution:
PM Agent's initial design competed with existing auto-activation for task routing,
creating confusion about orchestration responsibilities and adding unnecessary complexity.

Design Change:
Redefined PM Agent as a meta-layer agent that operates AFTER specialist agents
complete tasks, focusing on:
- Post-implementation documentation and pattern recording
- Immediate mistake analysis with prevention checklists
- Monthly documentation maintenance and noise reduction
- Pattern extraction and knowledge synthesis

Two-Layer Orchestration System:
1. Task Execution Layer: Existing auto-activation handles task routing (unchanged)
2. Self-Improvement Layer: PM Agent meta-layer handles documentation (new)

Files Modified:
- SuperClaude/Agents/pm-agent.md: Complete rewrite with meta-layer design
  - Category: orchestration → meta
  - Triggers: All user interactions → Post-implementation, mistakes, monthly
  - Behavioral Mindset: Continuous learning system
  - Self-Improvement Workflow: BEFORE/DURING/AFTER/MISTAKE RECOVERY/MAINTENANCE

- SuperClaude/Core/RULES.md: Agent Orchestration section updated
  - Split into Task Execution Layer + Self-Improvement Layer
  - Added orchestration flow diagram
  - Clarified PM Agent activates AFTER task completion

- README.md: Updated PM Agent description
  - "orchestrates all interactions" → "ensures continuous learning"

- Docs/User-Guide/agents.md: PM Agent section rewritten
  - Section: Orchestration Agent → Meta-Layer Agent
  - Expertise: Project orchestration → Self-improvement workflow executor
  - Examples: Task coordination → Post-implementation documentation

- PR_DOCUMENTATION.md: Comprehensive PR documentation added
  - Summary, motivation, changes, testing, breaking changes
  - Two-layer orchestration system diagram
  - Verification checklist

Integration Validated:
Tested with agiletec project's self-improvement-workflow.md:
 PM Agent aligns with existing BEFORE/DURING/AFTER/MISTAKE RECOVERY phases
 Complements (not competes with) existing workflow
 agiletec workflow defines WHAT, PM Agent defines WHO executes it

Breaking Changes: None
- Existing auto-activation continues unchanged
- Specialist agents unaffected
- User workflows remain the same
- New capability: Automatic documentation and knowledge maintenance

Value Proposition:
Transforms SuperClaude into a continuously learning system that accumulates
knowledge, prevents recurring mistakes, and maintains fresh documentation
without manual intervention.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* docs: add Claude Code conversation history management research

Research covering .jsonl file structure, performance impact, and retention policies.

Content:
- Claude Code .jsonl file format and message types
- Performance issues from GitHub (memory leaks, conversation compaction)
- Retention policies (consumer vs enterprise)
- Rotation recommendations based on actual data
- File history snapshot tracking mechanics

Source: Moved from agiletec project (research applicable to all Claude Code projects)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: add Development documentation structure

Phase 1: Documentation Structure complete

- Add Docs/Development/ directory for development documentation
- Add ARCHITECTURE.md - System architecture with PM Agent meta-layer
- Add ROADMAP.md - 5-phase development plan with checkboxes
- Add TASKS.md - Daily task tracking with progress indicators
- Add PROJECT_STATUS.md - Current status dashboard and metrics
- Add pm-agent-integration.md - Implementation guide for PM Agent mode

This establishes comprehensive documentation foundation for:
- System architecture understanding
- Development planning and tracking
- Implementation guidance
- Progress visibility

Related: #pm-agent-mode #documentation #phase-1

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: PM Agent session lifecycle and PDCA implementation

Phase 2: PM Agent Mode Integration (Design Phase)

Commands/pm.md updates:
- Add "Always-Active Foundation Layer" concept
- Add Session Lifecycle (Session Start/During Work/Session End)
- Add PDCA Cycle (Plan/Do/Check/Act) automation
- Add Serena MCP Memory Integration (list/read/write_memory)
- Document auto-activation triggers

Agents/pm-agent.md updates:
- Add Session Start Protocol (MANDATORY auto-activation)
- Add During Work PDCA Cycle with example workflows
- Add Session End Protocol with state preservation
- Add PDCA Self-Evaluation Pattern
- Add Documentation Strategy (temp → patterns/mistakes)
- Add Memory Operations Reference

Key Features:
- Session start auto-activation for context restoration
- 30-minute checkpoint saves during work
- Self-evaluation with think_about_* operations
- Systematic documentation lifecycle
- Knowledge evolution to CLAUDE.md

Implementation Status:
-  Design complete (Commands/pm.md, Agents/pm-agent.md)
-  Implementation pending (Core components)
-  Serena MCP integration pending

Salvaged from mistaken development in ~/.claude directory

Related: #pm-agent-mode #session-lifecycle #pdca-cycle #phase-2

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* fix: disable Serena MCP auto-browser launch

Disable web dashboard and GUI log window auto-launch in Serena MCP server
to prevent intrusive browser popups on startup. Users can still manually
access the dashboard at http://localhost:24282/dashboard/ if needed.

Changes:
- Add CLI flags to Serena run command:
  - --enable-web-dashboard false
  - --enable-gui-log-window false
- Ensures Git-tracked configuration (no reliance on ~/.serena/serena_config.yml)
- Aligns with AIRIS MCP Gateway integration approach

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* refactor: rename directories to lowercase for PEP8 compliance

- Rename superclaude/Agents -> superclaude/agents
- Rename superclaude/Commands -> superclaude/commands
- Rename superclaude/Core -> superclaude/core
- Rename superclaude/Examples -> superclaude/examples
- Rename superclaude/MCP -> superclaude/mcp
- Rename superclaude/Modes -> superclaude/modes

This change follows Python PEP8 naming conventions for package directories.

* style: fix PEP8 violations and update package name to lowercase

Changes:
- Format all Python files with black (43 files reformatted)
- Update package name from 'SuperClaude' to 'superclaude' in pyproject.toml
- Fix import statements to use lowercase package name
- Add missing imports (timedelta, __version__)
- Remove old SuperClaude.egg-info directory

PEP8 violations reduced from 2672 to 701 (mostly E501 line length due to black's 88 char vs flake8's 79 char limit).

* docs: add PM Agent development documentation

Add comprehensive PM Agent development documentation:
- PM Agent ideal workflow (7-phase autonomous cycle)
- Project structure understanding (Git vs installed environment)
- Installation flow understanding (CommandsComponent behavior)
- Task management system (current-tasks.md)

Purpose: Eliminate repeated explanations and enable autonomous PDCA cycles

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(pm-agent): add self-correcting execution and warning investigation culture

## Changes

### superclaude/commands/pm.md
- Add "Self-Correcting Execution" section with root cause analysis protocol
- Add "Warning/Error Investigation Culture" section enforcing zero-tolerance for dismissal
- Define error detection protocol: STOP → Investigate → Hypothesis → Different Solution → Execute
- Document anti-patterns (retry without understanding) and correct patterns (research-first)

### docs/Development/hypothesis-pm-autonomous-enhancement-2025-10-14.md
- Add PDCA workflow hypothesis document for PM Agent autonomous enhancement

## Rationale

PM Agent must never retry failed operations without understanding root causes.
All warnings and errors require investigation via context7/WebFetch/documentation
to ensure production-quality code and prevent technical debt accumulation.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(installer): add airis-mcp-gateway MCP server option

## Changes

- Add airis-mcp-gateway to MCP server options in installer
- Configuration: GitHub-based installation via uvx
- Repository: https://github.com/oraios/airis-mcp-gateway
- Purpose: Dynamic MCP Gateway for zero-token baseline and on-demand tool loading

## Implementation

Added to setup/components/mcp.py self.mcp_servers dictionary with:
- install_method: github
- install_command: uvx test installation
- run_command: uvx runtime execution
- required: False (optional server)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: kazuki <kazuki@kazukinoMacBook-Air.local>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-14 08:47:09 +05:30

17 KiB

SuperClaude Basic Examples Collection

Status: Status: Current - Essential commands, single-agent workflows, and common development tasks.

Quick Reference Guide: Copy-paste ready examples for beginners, focused on essential SuperClaude usage patterns and fundamental development workflows.

📝 Context Note: These examples show /sc: commands and @agent- invocations that trigger Claude Code to read specific context files and adopt the behaviors defined there. The sophistication comes from the behavioral instructions, not from executable software.

Overview and Usage Guide

Purpose: Essential SuperClaude commands and patterns for everyday development tasks. Start here for your first SuperClaude experience.

Target Audience: New users, developers learning SuperClaude fundamentals, immediate task application

Usage Pattern: Copy → Adapt → Execute → Learn from results

Key Features:

  • Examples demonstrate core SuperClaude functionality
  • Clear patterns for immediate application
  • Single-focus examples for clear learning
  • Progressive complexity within basic scope

Essential One-Liner Commands

Core Development Commands

Command: /sc:brainstorm

Purpose: Interactive project discovery and requirements gathering Syntax: /sc:brainstorm "project description" Example:

/sc:brainstorm "mobile app for fitness tracking"
# Expected: Socratic dialogue, requirement elicitation, feasibility analysis

Behavior: Triggers interactive discovery dialogue and requirements analysis

Command: /sc:analyze

Purpose: Analyze existing codebase for issues and improvements Syntax: /sc:analyze [target] --focus [domain] Example:

/sc:analyze src/ --focus security
# Expected: Comprehensive security audit, vulnerability report, improvement suggestions

Behavior: Provides comprehensive security analysis and improvement recommendations

Command: /sc:implement

Purpose: Implement a complete feature with best practices Syntax: /sc:implement "feature description with requirements" Example:

/sc:implement "user authentication with JWT and rate limiting"
# Expected: Complete auth implementation, security validation, tests included

Behavior: Delivers complete implementation following security and quality standards

Command: /sc:troubleshoot

Purpose: Troubleshoot and fix a problem systematically Syntax: /sc:troubleshoot "problem description" Example:

/sc:troubleshoot "API returns 500 error on user login"
# Expected: Step-by-step diagnosis, root cause identification, solution ranking

Verification: Activates root-cause-analyst + Sequential reasoning + systematic debugging

Command: /sc:test

Purpose: Generate comprehensive tests for existing code Syntax: /sc:test [target] --focus [domain] Example:

/sc:test --focus quality
# Expected: Test suite, quality metrics, coverage reporting

Verification: Activates quality-engineer + test automation

Quick Analysis Commands

Command: /sc:analyze (Quality Focus)

Purpose: Project structure and quality overview Syntax: /sc:analyze [target] --focus quality Example:

/sc:analyze . --focus quality

Verification:

Command: /sc:analyze (Security Focus)

Purpose: Security-focused code review Syntax: /sc:analyze [target] --focus security [--think] Example:

/sc:analyze src/ --focus security --think

Verification:

Command: /sc:analyze (Performance Focus)

Purpose: Performance bottleneck identification Syntax: /sc:analyze [target] --focus performance Example:

/sc:analyze api/ --focus performance

Verification:

Command: /sc:analyze (Architecture Focus)

Purpose: Architecture assessment for refactoring Syntax: /sc:analyze [target] --focus architecture [--serena] Example:

/sc:analyze . --focus architecture --serena

Verification:

Manual Agent Invocation Examples

Direct Specialist Activation

Pattern: @agent-[specialist]

Purpose: Manually invoke specific domain experts instead of auto-activation Syntax: @agent-[specialist] "task or question"

Python Expert

@agent-python-expert "optimize this data processing pipeline for performance"
# Expected: Python-specific optimizations, async patterns, memory management

Security Engineer

@agent-security "review this authentication system for vulnerabilities"
# Expected: OWASP compliance check, vulnerability assessment, secure coding recommendations

Frontend Architect

@agent-frontend-architect "design a responsive component architecture"
# Expected: Component patterns, state management, accessibility considerations

Quality Engineer

@agent-quality-engineer "create comprehensive test coverage for payment module"
# Expected: Test strategy, unit/integration/e2e tests, edge cases

Combining Auto and Manual Patterns

Pattern: Command + Manual Override

# Step 1: Use command with auto-activation
/sc:implement "user profile management system"
# Auto-activates: backend-architect, possibly frontend

# Step 2: Add specific expert review
@agent-security "review the profile system for data privacy compliance"
# Manual activation for targeted review

# Step 3: Performance optimization
@agent-performance-engineer "optimize database queries for profile fetching"
# Manual activation for specific optimization

Pattern: Sequential Specialist Chain

# Design phase
@agent-system-architect "design microservices architecture for e-commerce"

# Security review
@agent-security "review architecture for security boundaries"

# Implementation guidance
@agent-backend-architect "implement service communication patterns"

# DevOps setup
@agent-devops-architect "configure CI/CD for microservices"

Basic Usage Patterns

Discovery → Implementation Pattern

# Step 1: Explore and understand requirements
/sc:brainstorm "web dashboard for project management"
# Expected: Requirements discovery, feature prioritization, technical scope

# Step 2: Analyze technical approach
/sc:analyze "dashboard architecture patterns" --focus architecture --c7
# Expected: Architecture patterns, technology recommendations, implementation strategy

# Step 3: Implement core functionality
/sc:implement "React dashboard with task management and team collaboration"
# Expected: Complete dashboard implementation with modern React patterns

Development → Quality Pattern

# Step 1: Build the feature
/sc:implement "user registration with email verification"
# Expected: Registration system with email integration

# Step 2: Test thoroughly
/sc:test --focus quality
# Expected: Comprehensive test coverage and validation

# Step 3: Review and improve
/sc:analyze . --focus quality && /sc:implement "quality improvements"
# Expected: Quality assessment and targeted improvements

Problem → Solution Pattern

# Step 1: Understand the problem
/sc:troubleshoot "slow database queries on user dashboard"
# Expected: Systematic problem diagnosis and root cause analysis

# Step 2: Analyze affected components
/sc:analyze db/ --focus performance
# Expected: Database performance analysis and optimization opportunities

# Step 3: Implement solutions
/sc:implement "database query optimization and caching"
# Expected: Performance improvements with measurable impact

Getting Started Examples

Your First Project Analysis

# Complete project understanding workflow
/sc:load . && /sc:analyze --focus quality

# Expected Results:
# - Project structure analysis and documentation
# - Code quality assessment across all files
# - Architecture overview with component relationships
# - Security audit and performance recommendations

# Activates: Serena (project loading) + analyzer + security-engineer + performance-engineer
# Output: Comprehensive project report with actionable insights


# Variations for different focuses:
/sc:analyze src/ --focus quality          # Code quality only
/sc:analyze . --scope file               # Quick file analysis
/sc:analyze backend/ --focus security    # Backend security review

Interactive Requirements Discovery

# Transform vague ideas into concrete requirements
/sc:brainstorm "productivity app for remote teams"

# Expected Interaction:
# - Socratic questioning about user needs and pain points
# - Feature prioritization and scope definition
# - Technical feasibility assessment
# - Structured requirements document generation

# Activates: Brainstorming mode + system-architect + requirements-analyst
# Output: Product Requirements Document (PRD) with clear specifications

# Follow-up commands for progression:
/sc:analyze "team collaboration architecture" --focus architecture --c7
/sc:implement "real-time messaging system with React and WebSocket"

Simple Feature Implementation

# Complete authentication system
/sc:implement "user login with JWT tokens and password hashing"

# Expected Implementation:
# - Secure password hashing with bcrypt
# - JWT token generation and validation
# - Login/logout endpoints with proper error handling
# - Frontend login form with validation

# Activates: security-engineer + backend-architect + Context7
# Output: Production-ready authentication system


# Variations for different auth needs:
/sc:implement "OAuth integration with Google and GitHub"
/sc:implement "password reset flow with email verification"
/sc:implement "two-factor authentication with TOTP"

Common Development Tasks

API Development Basics

# REST API with CRUD operations
/sc:implement "Express.js REST API for blog posts with validation"
# Expected: Complete REST API with proper HTTP methods, validation, error handling


# API documentation generation
/sc:analyze api/ --focus architecture --c7
# Expected: Comprehensive API documentation with usage examples


# API testing setup
/sc:test --focus api --type integration
# Expected: Integration test suite for API endpoints

Frontend Component Development

# React component with modern patterns
/sc:implement "React user profile component with form validation and image upload"
# Activates: frontend-architect + Magic MCP + accessibility patterns
# Expected: Modern React component with hooks, validation, accessibility


# Component testing
/sc:test src/components/ --focus quality
# Expected: Component tests with React Testing Library


# Responsive design implementation
/sc:implement "responsive navigation component with mobile menu"
# Expected: Mobile-first responsive navigation with accessibility

Database Integration

# Database setup with ORM
/sc:implement "PostgreSQL integration with Prisma ORM and migrations"
# Expected: Database schema, ORM setup, migration system


# Database query optimization
/sc:analyze db/ --focus performance
# Expected: Query performance analysis and optimization suggestions


# Data validation and security
/sc:implement "input validation and SQL injection prevention"
# Expected: Comprehensive input validation and security measures

Basic Troubleshooting Examples

Common API Issues

# Performance problems
/sc:troubleshoot "API response time increased from 200ms to 2 seconds"
# Activates: root-cause-analyst + performance-engineer + Sequential reasoning
# Expected: Systematic diagnosis, root cause identification, solution ranking

# Authentication errors
/sc:troubleshoot "JWT token validation failing for valid users"
# Expected: Token validation analysis, security assessment, fix implementation

# Database connection issues
/sc:troubleshoot "database connection pool exhausted under load"
# Expected: Connection analysis, configuration fixes, scaling recommendations

Frontend Debugging

# React rendering issues
/sc:troubleshoot "React components not updating when data changes"
# Expected: State management analysis, re-rendering optimization, debugging guide

# Performance problems
/sc:troubleshoot "React app loading slowly with large component tree"
# Expected: Performance analysis, optimization strategies, code splitting recommendations

# Build failures
/sc:troubleshoot "webpack build failing with dependency conflicts"
# Expected: Dependency analysis, conflict resolution, build optimization

Development Environment Issues

# Setup problems
/sc:troubleshoot "Node.js application not starting after npm install"
# Expected: Environment analysis, dependency troubleshooting, configuration fixes

# Testing failures
/sc:troubleshoot "tests passing locally but failing in CI"
# Expected: Environment comparison, CI configuration analysis, fix recommendations

# Deployment issues
/sc:troubleshoot "application crashes on production deployment"
# Expected: Production environment analysis, configuration validation, deployment fixes

Copy-Paste Quick Solutions

Immediate Project Setup

# New React project with TypeScript
/sc:implement "React TypeScript project with routing, state management, and testing setup"
@agent-frontend-architect "review and optimize the project structure"

# New Node.js API server
/sc:implement "Express.js REST API with JWT authentication and PostgreSQL integration"
@agent-backend-architect "ensure scalability and best practices"

# Python web API
/sc:implement "FastAPI application with async PostgreSQL and authentication middleware"
@agent-python-expert "optimize async patterns and dependency injection"

# Next.js full-stack app
/sc:implement "Next.js 14 application with App Router, TypeScript, and Tailwind CSS"
@agent-system-architect "design optimal data fetching strategy"

Quick Quality Improvements

# Code quality enhancement
/sc:analyze . --focus quality && /sc:implement "code quality improvements"
@agent-quality-engineer "create quality metrics dashboard"

# Security hardening
/sc:analyze . --focus security && /sc:implement "security improvements"

# Test coverage improvement  
/sc:test --focus quality && /sc:implement "additional test coverage"

Common Feature Implementations

# User authentication system
/sc:implement "complete user authentication with registration, login, and password reset"

# File upload functionality
/sc:implement "secure file upload with image resizing and cloud storage"

# Real-time features
/sc:implement "real-time chat with WebSocket and message persistence"

# Payment processing
/sc:implement "Stripe payment integration with subscription management"

# Email functionality
/sc:implement "email service with templates and delivery tracking"

Basic Flag Examples

Analysis Depth Control

# Quick analysis
/sc:analyze src/ --scope file

# Standard analysis
/sc:analyze . --think

# Deep analysis
/sc:analyze . --think-hard --focus architecture

Focus Area Selection

# Security-focused analysis
/sc:analyze . --focus security


# Implementation with specific focus
/sc:implement "API optimization" --focus architecture


# Quality-focused testing
/sc:test --focus quality

Tool Integration

# Use Context7 for official patterns
/sc:implement "React hooks implementation" --c7


# Use Serena for project memory
/sc:analyze . --serena --focus architecture


# Efficient token usage
/sc:analyze large-project/ --uc

Learning Progression Workflow

Week 1: Foundation

# Day 1-2: Basic commands
/sc:analyze . --focus quality
/sc:implement "simple feature"
/sc:test --focus quality

# Day 3-4: Troubleshooting
/sc:troubleshoot "specific problem"
/sc:analyze problem-area/ --focus relevant-domain

# Day 5-7: Integration
/sc:brainstorm "project idea"
/sc:implement "core feature"
/sc:test --focus quality

Week 2: Patterns

# Workflow patterns
/sc:brainstorm → /sc:analyze → /sc:implement → /sc:test

# Problem-solving patterns
/sc:troubleshoot → /sc:analyze → /sc:implement

# Quality patterns
/sc:analyze → /sc:implement → /sc:test → /sc:analyze

Week 3-4: Integration

# Multi-step projects
/sc:brainstorm "larger project"
/sc:implement "phase 1"
/sc:test --focus quality
/sc:implement "phase 2"
/sc:test --focus integration

Next Steps

Ready for Intermediate?

  • Comfortable with all basic commands
  • Can complete simple workflows independently
  • Understanding of agent activation and tool selection
  • Ready for multi-step projects

Continue Learning:

  • Advanced Workflows: Complex orchestration and multi-agent coordination
  • Integration Patterns: Framework integration and cross-tool coordination
  • Best Practices Guide: Optimization strategies and expert techniques

Success Indicators:

  • Can solve common development problems independently
  • Understands when to use different flags and focuses
  • Can adapt examples to specific project needs
  • Ready to explore more complex SuperClaude capabilities

Remember: Start simple, practice frequently, and gradually increase complexity. These basic examples form the foundation for all advanced SuperClaude usage.