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sparc-methodology

Coordinate multi-agent software development across 17 SPARC modes.

Updated Mar 4, 2026
Search Tags:#tdd#development#architecture#multi-agent#orchestration#memory#sparc
One-click install
npx skills add https://github.com/script-repo/002-NXClaw --skill sparc-methodology-script-repo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sparc-methodology
Source: https://github.com/script-repo/002-NXClaw/tree/main/.claude/skills/sparc-methodology
Command: npx skills add https://github.com/script-repo/002-NXClaw --skill sparc-methodology-script-repo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

SPARC provides a structured, multi-phase framework for software development, enabling systematic planning, rigorous testing, and coordinated execution across multiple agents.

Core Features & Use Cases

  • 17 specialized modes for end-to-end development
  • Memory-integrated orchestration for cross-agent knowledge sharing
  • Clear phase transitions (Specification, Architecture, Refinement, Review, Completion)

Quick Start

Activate SPARC methodology to coordinate specification, architecture, refinement, and completion using multi-agent orchestration.

Frequently Asked Questions about sparc-methodology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is multi-agent orchestration for systematic software development?▼

Multi-agent orchestration coordinates specialized agents across development phases using memory integration to share knowledge, enabling systematic specification, architecture planning, and test-driven refinement.

How do I coordinate test-driven development across multiple agents?▼

You can coordinate test-driven development by applying a structured workflow that enforces disciplined specification, architecture planning, refinement, code review, and deployment monitoring using memory-coordinated agents.

When should I use a structured multi-phase development framework?▼

Use a structured multi-phase framework for end-to-end projects requiring rigorous testing, clear phase transitions, and coordinated execution across research, design, coding, testing, and deployment stages.

Does this multi-agent workflow support end-to-end project deployment?▼

Yes, the workflow applies to end-to-end projects across research, design, coding, testing, and deployment, enforcing deployment monitoring and completion phases through 17 specialized modes.

What's the best way to manage architecture planning and code review in parallel development?▼

The best way is using a systematic SPARC workflow that enforces disciplined specification and architecture planning, leveraging memory-integrated orchestration for cross-agent knowledge sharing during refinement and review.

Why does multi-agent development require memory integration?▼

Multi-agent development requires memory integration to enable cross-agent knowledge sharing, ensuring coordinated execution and consistent state transitions across specification, architecture, refinement, and completion phases.

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