What does the SPARC acronym stand for?

SPARC stands for Specification, Pseudocode, Architecture, Refinement, and Completion, representing the core phases of its systematic development methodology.

How does SPARC improve development speed?

It uses multi-agent orchestration and a 'batch-executor' mode to run tasks in parallel, achieving performance gains of 2.8x to 4.4x compared to sequential workflows.

Can I use SPARC for existing projects?

Yes, SPARC's 'reviewer', 'optimizer', and 'debugger' modes are ideal for analyzing and improving existing codebases, while the 'researcher' mode helps map out existing system architectures.

Does SPARC support Test-Driven Development?

Absolutely. SPARC includes a dedicated 'tdd' mode that enforces writing failing tests before implementation and iterates until coverage targets (e.g., 90%+) are met.

What is the role of the 'memory-manager' in this skill?

The memory-manager ensures that architectural decisions, research findings, and task progress are persisted across different agent sessions and tool executions.

SPARC Development Methodology

Name: SPARC Development Methodology
Author: ricable

byricable

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生産性とワークフロー

Implements a systematic five-phase development lifecycle using multi-agent orchestration for autonomous coding, testing, and architecture.

概要

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) is a comprehensive framework designed to optimize the software development lifecycle through 17 specialized AI agent modes. By integrating multi-agent orchestration with persistent memory, it enables developers to handle complex tasks—from deep research and system design to TDD-based implementation and security reviews—with high speed and architectural consistency. It is specifically built for Claude Flow to coordinate parallel execution and maintain high-quality standards across entire software projects.

主な機能

2 GitHub stars
Integrated memory management for persistent knowledge sharing across agents and sessions.
Multi-agent swarm coordination with parallel execution for 2.8-4.4x speed improvements.
17 specialized agent modes including Orchestrator, Coder, Architect, and TDD.
Full Test-Driven Development (TDD) support with automated red-green-refactor cycles.
Structured 5-phase methodology: Specification, Pseudocode, Architecture, Refinement, and Completion.

ユースケース

Orchestrating a swarm of specialized AI agents to perform simultaneous research, design, and implementation.
Applying strict quality control through automated multi-agent code reviews and performance profiling.
Automating the end-to-end development of microservices and complex API platforms.

概要

主な機能

2 GitHub stars
Integrated memory management for persistent knowledge sharing across agents and sessions.
Multi-agent swarm coordination with parallel execution for 2.8-4.4x speed improvements.
17 specialized agent modes including Orchestrator, Coder, Architect, and TDD.
Full Test-Driven Development (TDD) support with automated red-green-refactor cycles.
Structured 5-phase methodology: Specification, Pseudocode, Architecture, Refinement, and Completion.

ユースケース

Orchestrating a swarm of specialized AI agents to perform simultaneous research, design, and implementation.
Applying strict quality control through automated multi-agent code reviews and performance profiling.
Automating the end-to-end development of microservices and complex API platforms.