How does this improve development speed?

Through parallel execution and multi-agent coordination, SPARC can achieve 2.8x to 4.4x speed improvements by automating research, design, and testing concurrently.

What does SPARC stand for?

SPARC stands for Specification, Pseudocode, Architecture, Refinement, and Completion, representing the five key phases of this comprehensive development methodology.

Can I use SPARC for existing projects?

Yes, its 'Reviewer', 'Analyzer', and 'Debugger' modes are specifically designed to evaluate, refactor, and fix existing codebases using the structured SPARC approach.

Is TDD mandatory when using this skill?

While highly recommended and integrated into the 'Refinement' phase, the methodology is modular, allowing you to use specific modes like 'Coder' or 'Architect' independently of the full TDD workflow.

Does it support memory across sessions?

Yes, the 'Memory-Manager' mode ensures knowledge persistence and context preservation across different agent interactions and different development sessions.

SPARC Methodology & Multi-Agent Orchestrator

Name: SPARC Methodology & Multi-Agent Orchestrator
Author: ricable

byricable

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생산성 및 워크플로

Implements a structured 5-phase development framework using 17 specialized AI agents to automate software engineering from research to deployment.

소개

The SPARC methodology provides a comprehensive development lifecycle—Specification, Pseudocode, Architecture, Refinement, and Completion—integrated with Claude Flow's multi-agent orchestration. By coordinating specialized agents like architects, coders, and testers, it enables systematic, test-driven development (TDD) with parallel execution capabilities that significantly increase development velocity. It is ideal for developers building complex systems who need a structured AI-driven workflow that ensures code quality, architectural integrity, and persistent project memory across the entire software development life cycle.

주요 기능

Multi-agent orchestration for parallel task execution and high throughput
17 specialized AI modes including Coder, Architect, and Swarm Coordinator
Systematic 5-phase development lifecycle from Specification to Completion
Native Test-Driven Development (TDD) workflows with red-green-refactor cycles
Persistent knowledge management with cross-session memory integration
2 GitHub stars

사용 사례

Architecting and implementing complex microservices with automated documentation
Executing high-speed TDD cycles for rapid and reliable feature development
Managing large-scale code reviews and security audits across entire repositories

소개

주요 기능

Multi-agent orchestration for parallel task execution and high throughput
17 specialized AI modes including Coder, Architect, and Swarm Coordinator
Systematic 5-phase development lifecycle from Specification to Completion
Native Test-Driven Development (TDD) workflows with red-green-refactor cycles
Persistent knowledge management with cross-session memory integration
2 GitHub stars

사용 사례

Architecting and implementing complex microservices with automated documentation
Executing high-speed TDD cycles for rapid and reliable feature development
Managing large-scale code reviews and security audits across entire repositories