SP

sparc-methodology

Structures software development into five phases to improve output quality through multi-agent orchestration.

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Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
140 chars · catalog descriptionno explicit “when” trigger
Intermediate

Key capabilities

  • Decompose complex software tasks into systematic development phases
  • Execute parallel agent coordination for multi-agent workflows
  • Implement test-driven development cycles with automated validation
  • Perform batch file operations and code refactoring
  • Manage persistent cross-session memory for architectural decisions
  • Conduct automated code quality, security, and performance reviews

How it works

The methodology uses 17 specialized modes to orchestrate agents through five distinct phases: Specification, Pseudocode, Architecture, Refinement, and Completion. It utilizes parallel execution and memory integration to maintain consistency and speed across development tasks.

Inputs & outputs

You give it
Task description string provided to a specific SPARC mode or pipeline
You get back
Generated code, architectural documentation, or test reports

When to use sparc-methodology

  • Planning a new software project
  • Ensuring TDD standards during dev
  • Structuring multi-agent coding workflows

About this skill

SPARC Methodology - Comprehensive Development Framework

Overview

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) is a systematic development methodology integrated with Claude Flow's multi-agent orchestration capabilities. It provides 17 specialized modes for comprehensive software development, from initial research through deployment and monitoring.

Table of Contents

  1. Core Philosophy
  2. Development Phases
  3. Available Modes
  4. Activation Methods
  5. Orchestration Patterns
  6. TDD Workflows
  7. Best Practices
  8. Integration Examples
  9. Common Workflows

Core Philosophy

SPARC methodology emphasizes:

  • Systematic Approach: Structured phases from specification to completion
  • Test-Driven Development: Tests written before implementation
  • Parallel Execution: Concurrent agent coordination for 2.8-4.4x speed improvements
  • Memory Integration: Persistent knowledge sharing across agents and sessions
  • Quality First: Comprehensive reviews, testing, and validation
  • Modular Design: Clean separation of concerns with clear interfaces

Key Principles

  1. Specification Before Code: Define requirements and constraints clearly
  2. Design Before Implementation: Plan architecture and components
  3. Tests Before Features: Write failing tests, then make them pass
  4. Review Everything: Code quality, security, and performance checks
  5. Document Continuously: Maintain current documentation throughout

Development Phases

Phase 1: Specification

Goal: Define requirements, constraints, and success criteria

  • Requirements analysis
  • User story mapping
  • Constraint identification
  • Success metrics definition
  • Pseudocode planning

Key Modes: researcher, analyzer, memory-manager

Phase 2: Architecture

Goal: Design system structure and component interfaces

  • System architecture design
  • Component interface definition
  • Database schema planning
  • API contract specification
  • Infrastructure planning

Key Modes: architect, designer, orchestrator

Phase 3: Refinement (TDD Implementation)

Goal: Implement features with test-first approach

  • Write failing tests
  • Implement minimum viable code
  • Make tests pass
  • Refactor for quality
  • Iterate until complete

Key Modes: tdd, coder, tester

Phase 4: Review

Goal: Ensure code quality, security, and performance

  • Code quality assessment
  • Security vulnerability scanning
  • Performance profiling
  • Best practices validation
  • Documentation review

Key Modes: reviewer, optimizer, debugger

Phase 5: Completion

Goal: Integration, deployment, and monitoring

  • System integration
  • Deployment automation
  • Monitoring setup
  • Documentation finalization
  • Knowledge capture

Key Modes: workflow-manager, documenter, memory-manager


Available Modes

Core Orchestration Modes

orchestrator

Multi-agent task orchestration with TodoWrite/Task/Memory coordination.

Capabilities:

  • Task decomposition into manageable units
  • Agent coordination and resource allocation
  • Progress tracking and result synthesis
  • Adaptive strategy selection
  • Cross-agent communication

Usage:

mcp__claude-flow__sparc_mode {
  mode: "orchestrator",
  task_description: "coordinate feature development",
  options: { parallel: true, monitor: true }
}

swarm-coordinator

Specialized swarm management for complex multi-agent workflows.

Capabilities:

  • Topology optimization (mesh, hierarchical, ring, star)
  • Agent lifecycle management
  • Dynamic scaling based on workload
  • Fault tolerance and recovery
  • Performance monitoring

workflow-manager

Process automation and workflow orchestration.

Capabilities:

  • Workflow definition and execution
  • Event-driven triggers
  • Sequential and parallel pipelines
  • State management
  • Error handling and retry logic

batch-executor

Parallel task execution for high-throughput operations.

Capabilities:

  • Concurrent file operations
  • Batch processing optimization
  • Resource pooling
  • Load balancing
  • Progress aggregation

Development Modes

coder

Autonomous code generation with batch file operations.

Capabilities:

  • Feature implementation
  • Code refactoring
  • Bug fixes and patches
  • API development
  • Algorithm implementation

Quality Standards:

  • ES2022+ standards
  • TypeScript type safety
  • Comprehensive error handling
  • Performance optimization
  • Security best practices

Usage:

mcp__claude-flow__sparc_mode {
  mode: "coder",
  task_description: "implement user authentication with JWT",
  options: {
    test_driven: true,
    parallel_edits: true,
    typescript: true
  }
}

architect

System design with Memory-based coordination.

Capabilities:

  • Microservices architecture
  • Event-driven design
  • Domain-driven design (DDD)
  • Hexagonal architecture
  • CQRS and Event Sourcing

Memory Integration:

  • Store architectural decisions
  • Share component specifications
  • Maintain design consistency
  • Track architectural evolution

Design Patterns:

  • Layered architecture
  • Microservices patterns
  • Event-driven patterns
  • Domain modeling
  • Infrastructure as Code

Usage:

mcp__claude-flow__sparc_mode {
  mode: "architect",
  task_description: "design scalable e-commerce platform",
  options: {
    detailed: true,
    memory_enabled: true,
    patterns: ["microservices", "event-driven"]
  }
}

tdd

Test-driven development with comprehensive testing.

Capabilities:

  • Test-first development
  • Red-green-refactor cycle
  • Test suite design
  • Coverage optimization (target: 90%+)
  • Continuous testing

TDD Workflow:

  1. Write failing test (RED)
  2. Implement minimum code
  3. Make test pass (GREEN)
  4. Refactor for quality (REFACTOR)
  5. Repeat cycle

Testing Strategies:

  • Unit testing (Jest, Mocha, Vitest)
  • Integration testing
  • End-to-end testing (Playwright, Cypress)
  • Performance testing
  • Security testing

Usage:

mcp__claude-flow__sparc_mode {
  mode: "tdd",
  task_description: "shopping cart feature with payment integration",
  options: {
    coverage_target: 90,
    test_framework: "jest",
    e2e_framework: "playwright"
  }
}

reviewer

Code review using batch file analysis.

Capabilities:

  • Code quality assessment
  • Security vulnerability detection
  • Performance analysis
  • Best practices validation
  • Documentation review

Review Criteria:

  • Code correctness and logic
  • Design pattern adherence
  • Comprehensive error handling
  • Test coverage adequacy
  • Maintainability and readability
  • Security vulnerabilities
  • Performance bottlenecks

Batch Analysis:

  • Parallel file review
  • Pattern detection
  • Dependency checking
  • Consistency validation
  • Automated reporting

Usage:

mcp__claude-flow__sparc_mode {
  mode: "reviewer",
  task_description: "review authentication module PR #123",
  options: {
    security_check: true,
    performance_check: true,
    test_coverage_check: true
  }
}

Analysis and Research Modes

researcher

Deep research with parallel WebSearch/WebFetch and Memory coordination.

Capabilities:

  • Comprehensive information gathering
  • Source credibility evaluation
  • Trend analysis and forecasting
  • Competitive research
  • Technology assessment

Research Methods:

  • Parallel web searches
  • Academic paper analysis
  • Industry report synthesis
  • Expert opinion gathering
  • Statistical data compilation

Memory Integration:

  • Store research findings with citations
  • Build knowledge graphs
  • Track information sources
  • Cross-reference insights
  • Maintain research history

Usage:

mcp__claude-flow__sparc_mode {
  mode: "researcher",
  task_description: "research microservices best practices 2024",
  options: {
    depth: "comprehensive",
    sources: ["academic", "industry", "news"],
    citations: true
  }
}

analyzer

Code and data analysis with pattern recognition.

Capabilities:

  • Static code analysis
  • Dependency analysis
  • Performance profiling
  • Security scanning
  • Data pattern recognition

optimizer

Performance optimization and bottleneck resolution.

Capabilities:

  • Algorithm optimization
  • Database query tuning
  • Caching strategy design
  • Bundle size reduction
  • Memory leak detection

Creative and Support Modes

designer

UI/UX design with accessibility focus.

Capabilities:

  • Interface design
  • User experience optimization
  • Accessibility compliance (WCAG 2.1)
  • Design system creation
  • Responsive layout design

innovator

Creative problem-solving and novel solutions.

Capabilities:

  • Brainstorming and ideation
  • Alternative approach generation
  • Technology evaluation
  • Proof of concept development
  • Innovation feasibility analysis

documenter

Comprehensive documentation generation.

Capabilities:

  • API documentation (OpenAPI/Swagger)
  • Architecture diagrams
  • User guides and tutorials
  • Code comments and JSDoc
  • README and changelog maintenance

debugger

Systematic debugging and issue resolution.

Capabilities:

  • Bug reproduction
  • Root cause analysis
  • Fix implementation
  • Regression prevention
  • Debug logging optimization

tester

Comprehensive testing beyond TDD.

Capabilities:

  • Test suite expansion
  • Edge case identification
  • Performance testing
  • Load testing
  • Chaos engineering

memory-manager

Knowledge management and context preservation.

Capabilities:

  • Cross-session memory persistence
  • Knowledge graph construction
  • Context restoration
  • Learning pattern extraction
  • Decision tracking

Activation Methods

Method 1: MCP Tools (Preferred in Claude


Content truncated.

When not to use it

  • Simple scripts that do not require architectural planning or multi-agent orchestration
  • Projects where test-driven development or strict quality standards are not required

Prerequisites

Claude Flow environmentNode.js environment for npx execution

Limitations

  • Requires adherence to specific SPARC modes and workflow structures
  • Performance benefits depend on the ability to parallelize tasks

How it compares

Unlike manual development, this methodology automates the entire lifecycle through predefined agent modes and cross-agent communication, enabling concurrent task processing and persistent knowledge sharing.

Compared to similar skills

sparc-methodology side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
sparc-methodology (this skill)84moReviewIntermediate
create-plan368moReviewBeginner
project-planner329moReviewIntermediate
system-design199moNo flagsIntermediate

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