sparc-methodology

Orchestrates multi-agent software development using the SPARC phased methodology with TDD workflows.

Updated Mar 25, 2026
One-click install
npx skills add https://github.com/dmuhoro/EasyTutor --skill sparc-methodology-dmuhoro
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sparc-methodology
Source: https://github.com/dmuhoro/EasyTutor/tree/main/archive/.claude/skills/sparc-methodology
Command: npx skills add https://github.com/dmuhoro/EasyTutor --skill sparc-methodology-dmuhoro

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Coordinating complex software development across specification, architecture, implementation, testing, and review phases is error-prone when done ad hoc. This Skill provides a structured SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) methodology with 17 specialized modes and multi-agent orchestration via Claude Flow. ## Core Features & Use Cases - Phased Development Framework: Five defined phases from specification through completion, each mapped to specialized modes like researcher, architect, coder, tdd, and reviewer. - Multi-Agent Orchestration: Swarm initialization with hierarchical, mesh, ring, or star topologies, parallel agent execution, and cross-agent memory sharing. - TDD Workflows: Red-green-refactor cycles with coverage targets (90%+), supporting Jest, Vitest, Playwright, and Cypress. - Use Case: Building a full-stack feature — run the researcher mode to gather requirements, architect to design the system, coder with test_driven options to implement, then reviewer for security and performance checks, all coordinated through MCP tools or the npx claude-flow CLI. ## Quick Start Ask the AI to run the SPARC pipeline for your feature, for example: use the sparc methodology to design, implement, and test a user authentication feature with JWT.

Frequently Asked Questions about sparc-methodology

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

FAQPage Schema
How do I run a SPARC mode with Claude Flow?

Run a SPARC mode using the MCP tool mcp__claude-flow__sparc_mode with a mode name and task description, or via CLI with npx claude-flow sparc run <mode> "task". List all modes with npx claude-flow sparc modes.

What are the SPARC development phases?

SPARC has five phases: Specification (requirements and pseudocode), Architecture (system and interface design), Refinement (TDD implementation), Review (quality, security, performance checks), and Completion (integration, deployment, documentation).

How does test-driven development work in SPARC?

SPARC's tdd mode follows the red-green-refactor cycle: write a failing test, implement minimal code to pass it, then refactor. It targets 90%+ coverage and supports Jest, Mocha, Vitest, Playwright, and Cypress.

Can I run multiple SPARC agents in parallel?

Yes. Initialize a swarm with mcp__claude-flow__swarm_init using hierarchical, mesh, ring, or star topology, then spawn agents in a single message. Parallel execution provides 2.8-4.4x speed improvements according to the documentation.

What is the difference between MCP tools and the npx CLI for SPARC?

MCP tools (mcp__claude-flow__*) are preferred inside Claude Code for full orchestration with swarm monitoring and memory. The npx claude-flow CLI is the fallback for terminal usage or when MCP tools are unavailable.

When should I not use the SPARC methodology?

SPARC adds coordination overhead through multi-phase workflows and agent orchestration, so it is poorly suited for trivial single-file edits or quick one-off scripts where direct implementation is faster.