sparc-methodology

Coordinate software development from specification to completion using SPARC phases.

Updated Sep 20, 2024
One-click install
npx skills add https://github.com/nahtonaj/dotfiles --skill sparc-methodology-nahtonaj
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sparc-methodology
Source: https://github.com/nahtonaj/dotfiles/tree/main/.claude/skills/sparc-methodology
Command: npx skills add https://github.com/nahtonaj/dotfiles --skill sparc-methodology-nahtonaj

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

SPARC provides a structured, multi-phase framework for assembling software from specification through completion using parallel agent orchestration.

Core Features & Use Cases

  • Phase-driven methodology (Specification, Pseudocode, Architecture, Refinement, Completion) with cross-agent coordination
  • Memory integration and memory sharing across agents and sessions
  • Optional modes for researchers, architects, coders, testers, reviewers, and memory-managers to cover end-to-end workflows
  • Best practices for TDD, design reviews, deployment and monitoring across larger teams

Quick Start

Initiate SPARC workflow to coordinate a feature development from research to deployment.

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 software development?▼

Multi-agent orchestration coordinates parallel agents across systematic development phases from specification to completion. It structures workflows using specialized modes like researcher, architect, coder, and reviewer to handle distinct tasks within a unified project lifecycle.

How do I coordinate TDD and architecture workflows end-to-end?▼

You coordinate TDD and architecture workflows by applying a phase-driven methodology spanning specification, pseudocode, architecture, refinement, and completion. This approach integrates rigorous testing and design reviews across cross-agent coordination for systematic assembly.

Can I share memory context across different agents and sessions?▼

Yes, memory integration enables sharing context across agents and sessions. The memory-manager mode handles this by persisting information throughout the workflow, ensuring all orchestrated agents maintain a cohesive understanding of the project state.

What's the best way to structure a phase-driven development workflow?▼

The best way to structure phase-driven development is using the SPARC methodology, which sequences projects through specification, pseudocode, architecture, refinement, and completion. This framework ensures cross-agent coordination and best practices for TDD and deployment.

Does multi-agent orchestration support dedicated reviewer and optimizer roles?▼

Yes, multi-agent orchestration supports optional modes specifically for reviewers and optimizers. These roles handle design reviews and performance refinement, ensuring end-to-end workflows maintain rigorous architecture patterns and quality standards before deployment.

When do I need parallel agent orchestration for software projects?▼

You need parallel agent orchestration for larger teams and projects requiring rigorous TDD, design reviews, and systematic software assembly. It is essential when coordinating complex, multi-phase workflows from initial research through final deployment.