Coordinate multi-agent software development through SPARC phases with TDD.
npx skills add https://github.com/whrit/agent-flow --skill sparc-methodology-whrit
Please help me install this Agent Skill. Skill: sparc-methodology Source: https://github.com/whrit/agent-flow/tree/main/.claude/skills/sparc-methodology Command: npx skills add https://github.com/whrit/agent-flow --skill sparc-methodology-whrit
This Skill provides a structured solution to unstructured software development, ensuring consistency, quality, and efficiency across all phases. It integrates multi-agent AI orchestration to accelerate development by 2.8-4.4x, reduce tokens, and maintain high test coverage.
Execute a specific SPARC mode like coder for "implement user authentication with JWT" using mcp__claude-flow__sparc_mode({ mode: "coder", task_description: "implement user authentication with JWT", options: { test_driven: true } }).
High-intent search queries and answers about installing and using this skill.
Multi-agent orchestration coordinates specialized AI agents across development phases using hierarchical, mesh, sequential, and parallel patterns. SPARC methodology structures this coordination through 17 AI modes, enabling parallel execution, memory sharing, and accelerated development by 2.8–4.4x while reducing token consumption.
Test-driven development writes failing tests first, then minimal code to pass them, enforcing quality gates upfront. SPARC integrates TDD across the Refinement phase with continuous security and performance checks, maintaining 90%+ test coverage and reducing bugs before deployment.
SPARC methodology guides projects through five phases—Specification, Pseudocode, Architecture, Refinement (TDD), and Completion—with explicit mode definitions, API contracts, and cross-agent communication. This phase-driven governance ensures consistency and enables iterative refinement at each stage.
Yes, SPARC integrates claude-flow as its core dependency for multi-agent orchestration. You invoke specific SPARC modes like 'coder' via claude-flow to execute tasks with test-driven workflows and structured communication between agents.
Use SPARC for end-to-end projects requiring parallel multi-agent coordination, high test coverage, and quality assurance across research through deployment. It suits complex feature development, architecture design, and scenarios where consistency, efficiency, and AI-driven reviews prevent rework.
Multi-agent systems require careful mode selection, explicit communication contracts, and memory synchronization to avoid divergent outputs. SPARC mitigates these through hierarchical governance and persistent memory sharing, but complex workflows still demand structured task definitions and iterative refinement.
CornjebusCoordinate multi-agent software development across SPARC phases and 17 modes.
jay6697117Expertly-designed AI system capable of delivering flawless, high-speed performance across all tasks with zero errors, instantly adapting to meet every user's needs perfectly.
gztcodeAutomate code review with static security scanning, quality gates, and an independent reviewer subagent.
LuisSambranoOrchestrate red-green-refactor TDD workflows with multi-agent coordination.
