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sparc-methodology

Coordinate specification, pseudocode, architecture, refinement, and completion across multi-agent orchestration.

Updated Jul 2, 2025
Search Tags:#workflow#tdd#architecture#multi-agent#orchestration#sparc
One-click install
npx skills add https://github.com/dug-21/neural-data-platform --skill sparc-methodology-dug-21
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sparc-methodology
Source: https://github.com/dug-21/neural-data-platform/tree/main/.claude/skills/sparc-methodology
Command: npx skills add https://github.com/dug-21/neural-data-platform --skill sparc-methodology-dug-21

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

SPARC provides a systematic, end-to-end development methodology designed to coordinate specification, pseudocode, architecture, refinement, and completion using Claude Flow's multi-agent orchestration capabilities.

Core Features & Use Cases

  • Structured Phases: Defines specification, design, implementation, testing, review, and deployment as distinct, repeatable phases.
  • Multi-Agent Orchestration: Enables parallel collaboration across agents (researcher, architect, coder, tdd, reviewer, optimizer, documenter, memory-manager) to accelerate delivery.
  • Memory & Hooks: Supports cross-session memory and lifecycle hooks to preserve decisions and automate workflows.
  • Use Case: Apply SPARC to a new feature from requirements gathering through deployment with traceable artifacts and metrics.

Quick Start

Execute a sample SPARC workflow:

  • Initialize swarm: mcp__claude-flow__swarm_init { topology: "hierarchical" }
  • Start research: mcp__claude-flow__sparc_mode { mode: "researcher", task_description: "gather requirements" }
  • Design: mcp__claude-flow__sparc_mode { mode: "architect", task_description: "design system" }
  • Implement: mcp__claude-flow__sparc_mode { mode: "coder", task_description: "implement feature" }
  • Test: mcp__claude-flow__sparc_mode { mode: "tdd", task_description: "write tests" }
  • Review: mcp__claude-flow__sparc_mode { mode: "reviewer", task_description: "code review" }

Frequently Asked Questions about sparc-methodology

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

FAQPage Schema
How do I coordinate parallel multi-agent workflows for structured software development?▼

Multi-agent orchestration coordinates parallel collaboration across specialized roles like researcher, architect, coder, and reviewer to accelerate software delivery. SPARC methodology structures this into distinct phases from specification through deployment with traceable artifacts.

What is the SPARC methodology for software engineering?▼

SPARC is a systematic development methodology coordinating specification, pseudocode, architecture, refinement, and completion. It defines repeatable phases including specification, design, implementation, testing, review, and deployment to structure end-to-end software projects.

How do I run test-driven development within a multi-agent orchestration system?▼

Test-driven development runs as a distinct phase by initiating the TDD mode within the orchestration swarm. You pass a task description to write tests, which executes in parallel with other specialized modes like coder and reviewer to accelerate delivery.

Can I use Claude Flow to orchestrate architecture design and code review simultaneously?▼

Claude Flow orchestrates architecture design and code review simultaneously by spawning parallel agents. You initialize a hierarchical swarm topology and assign distinct modes like architect for system design and reviewer for code review to enable parallel collaboration.

Does multi-agent development workflow support cross-session memory and lifecycle hooks?▼

Multi-agent development workflows support cross-session memory to preserve decisions and lifecycle hooks to automate workflows. This integration maintains context across phases from research through deployment, ensuring traceable artifacts and metrics.

When should I not use a structured multi-agent orchestration workflow?▼

Structured multi-agent orchestration is not suited for simple, single-file tasks lacking distinct specification, architecture, and testing phases. It targets scalable software projects requiring structured phases, parallel collaboration, and memory integration from research to deployment.

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