/sparc-modes
SPARC (Specification, Planning, Architecture, Review, Code) is a comprehensive development methodology with 17 specialized modes, all integrated with MCP tools for enhanced coordination and execution.
$ npx -y skills add spencermarx/open-code-review --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/sparc-modes
Context preview
What this command does when you run it.
SPARC (Specification, Planning, Architecture, Review, Code) is a comprehensive development methodology with 17 specialized modes, all integrated with MCP tools for enhanced coordination and execution.
Command definition
sparc-modes.mdSPARC Modes Overview
SPARC (Specification, Planning, Architecture, Review, Code) is a comprehensive development methodology with 17 specialized modes, all integrated with MCP tools for enhanced coordination and execution.
Available Modes
Core Orchestration Modes
- **orchestrator**: Multi-agent task orchestration
- **swarm-coordinator**: Specialized swarm management
- **workflow-manager**: Process automation
- **batch-executor**: Parallel task execution
Development Modes
- **coder**: Autonomous code generation
- **architect**: System design
- **reviewer**: Code review
- **tdd**: Test-driven development
Analysis and Research Modes
- **researcher**: Deep research capabilities
- **analyzer**: Code and data analysis
- **optimizer**: Performance optimization
Creative and Support Modes
- **designer**: UI/UX design
- **innovator**: Creative problem solving
- **documenter**: Documentation generation
- **debugger**: Systematic debugging
- **tester**: Comprehensive testing
- **memory-manager**: Knowledge management
Usage
Option 1: Using MCP Tools (Preferred in Claude Code)
// Execute SPARC mode directly
mcp__claude-flow__sparc_mode {
mode: "<mode>",
task_description: "<task>",
options: {
// mode-specific options
}
}
// Initialize swarm for advanced coordination
mcp__claude-flow__swarm_init {
topology: "hierarchical",
strategy: "auto",
maxAgents: 8
}
// Spawn specialized agents
mcp__claude-flow__agent_spawn {
type: "<agent-type>",
capabilities: ["<capability1>", "<capability2>"]
}
// Monitor execution
mcp__claude-flow__swarm_monitor {
swarmId: "current",
interval: 5000
}Option 2: Using NPX CLI (Fallback when MCP not available)
# Use when running from terminal or MCP tools unavailable
npx claude-flow sparc run <mode> "task description"
# For alpha features
npx claude-flow@alpha sparc run <mode> "task description"
# List all modes
npx claude-flow sparc modes
# Get help for a mode
npx claude-flow sparc help <mode>
# Run with options
npx claude-flow sparc run <mode> "task" --parallel --monitor
Option 3: Local Installation
# If claude-flow is installed locally
./claude-flow sparc run <mode> "task description"
Common Workflows
Full Development Cycle
Using MCP Tools (Preferred)
// 1. Initialize development swarm
mcp__claude-flow__swarm_init {
topology: "hierarchical",
maxAgents: 12
}
// 2. Architecture design
mcp__claude-flow__sparc_mode {
mode: "architect",
task_description: "design microservices"
}
// 3. Implementation
mcp__claude-flow__sparc_mode {
mode: "coder",
task_description: "implement services"
}
// 4. Testing
mcp__claude-flow__sparc_mode {
mode: "tdd",
task_description: "test all services"
}
// 5. Review
mcp__claude-flow__sparc_mode {
mode: "reviewer",
task_description: "review implementation"
}Using NPX CLI (Fallback)
# 1. Architecture design
npx claude-flow sparc run architect "design microservices"
# 2. Implementation
npx claude-flow sparc run coder "implement services"
# 3. Testing
npx claude-flow sparc run tdd "test all services"
# 4. Review
npx claude-flow sparc run reviewer "review implementation"
Research and Innovation
Using MCP Tools (Preferred)
// 1. Research phase
mcp__claude-flow__sparc_mode {
mode: "researcher",
task_description: "research best practices"
}
// 2. Innovation
mcp__claude-flow__sparc_mode {
mode: "innovator",
task_description: "propose novel solutions"
}
// 3. Documentation
mcp__claude-flow__sparc_mode {
mode: "documenter",
task_description: "document findings"
}Using NPX CLI (Fallback)
# 1. Research phase
npx claude-flow sparc run researcher "research best practices"
# 2. Innovation
npx claude-flow sparc run innovator "propose novel solutions"
# 3. Documentation
npx claude-flow sparc run documenter "document findings"
Read more
SPARC Modes Overview
SPARC (Specification, Planning, Architecture, Review, Code) is a comprehensive development methodology with 17 specialized modes, all integrated with MCP tools for enhanced coordination and execution.
Available Modes
Core Orchestration Modes
- **orchestrator**: Multi-agent task orchestration
- **swarm-coordinator**: Specialized swarm management
- **workflow-manager**: Process automation
- **batch-executor**: Parallel task execution
Development Modes
- **coder**: Autonomous code generation
- **architect**: System design
- **reviewer**: Code review
- **tdd**: Test-driven development
Analysis and Research Modes
- **researcher**: Deep research capabilities
- **analyzer**: Code and data analysis
- **optimizer**: Performance optimization
Creative and Support Modes
- **designer**: UI/UX design
- **innovator**: Creative problem solving
- **documenter**: Documentation generation
- **debugger**: Systematic debugging
- **tester**: Comprehensive testing
- **memory-manager**: Knowledge management
Usage
Option 1: Using MCP Tools (Preferred in Claude Code)
// Execute SPARC mode directly
mcp__claude-flow__sparc_mode {
mode: "<mode>",
task_description: "<task>",
options: {
// mode-specific options
}
}
// Initialize swarm for advanced coordination
mcp__claude-flow__swarm_init {
topology: "hierarchical",
strategy: "auto",
maxAgents: 8
}
// Spawn specialized agents
mcp__claude-flow__agent_spawn {
type: "<agent-type>",
capabilities: ["<capability1>", "<capability2>"]
}
// Monitor execution
mcp__claude-flow__swarm_monitor {
swarmId: "current",
interval: 5000
}Option 2: Using NPX CLI (Fallback when MCP not available)
# Use when running from terminal or MCP tools unavailable npx claude-flow sparc run <mode> "task description" # For alpha features npx claude-flow@alpha sparc run <mode> "task description" # List all modes npx claude-flow sparc modes # Get help for a mode npx claude-flow sparc help <mode> # Run with options npx claude-flow sparc run <mode> "task" --parallel --monitor
Option 3: Local Installation
# If claude-flow is installed locally ./claude-flow sparc run <mode> "task description"
Common Workflows
Full Development Cycle
Using MCP Tools (Preferred)
// 1. Initialize development swarm
mcp__claude-flow__swarm_init {
topology: "hierarchical",
maxAgents: 12
}
// 2. Architecture design
mcp__claude-flow__sparc_mode {
mode: "architect",
task_description: "design microservices"
}
// 3. Implementation
mcp__claude-flow__sparc_mode {
mode: "coder",
task_description: "implement services"
}
// 4. Testing
mcp__claude-flow__sparc_mode {
mode: "tdd",
task_description: "test all services"
}
// 5. Review
mcp__claude-flow__sparc_mode {
mode: "reviewer",
task_description: "review implementation"
}Using NPX CLI (Fallback)
# 1. Architecture design npx claude-flow sparc run architect "design microservices" # 2. Implementation npx claude-flow sparc run coder "implement services" # 3. Testing npx claude-flow sparc run tdd "test all services" # 4. Review npx claude-flow sparc run reviewer "review implementation"
Research and Innovation
Using MCP Tools (Preferred)
// 1. Research phase
mcp__claude-flow__sparc_mode {
mode: "researcher",
task_description: "research best practices"
}
// 2. Innovation
mcp__claude-flow__sparc_mode {
mode: "innovator",
task_description: "propose novel solutions"
}
// 3. Documentation
mcp__claude-flow__sparc_mode {
mode: "documenter",
task_description: "document findings"
}Using NPX CLI (Fallback)
# 1. Research phase npx claude-flow sparc run researcher "research best practices" # 2. Innovation npx claude-flow sparc run innovator "propose novel solutions" # 3. Documentation npx claude-flow sparc run documenter "document findings"
AI-powered multi-agent code review. Simulates a customizable team of Engineers performing code review with built-in discourse.
Repo: spencermarx/open-code-review
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