Agent skill · software engineering · aiskillstore

sparc-methodology

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

Why this skill is useful

Adds comprehensive multi-agent orchestration scripts and specialized workflows for software development that are not commonly found in public documentation.

What it needs

Requires claude-flow installed locally. About 10k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.

What this skill does

SPARC Methodology - Comprehensive Development Framework Overview SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) is a systematic development methodology integrated with Claude Flow's multi-agent orchestration capabilities. It provides 17 specialized modes for comprehensive software development, from initial research through deployment and monitoring. Table of Contents 1. Core Philosophy 2. Development Phases 3. Available Modes 4. Activation Methods 5. Orchestration Patterns 6. TDD Workflows 7. Best Practices 8. Integration Examples 9. Common Workflows --- Core Philosophy SPARC methodology emphasizes: Systematic Approach: Structured phases from specification to completion Test-Driven Development: Tests written before implementation Parallel Execution: Concurrent agent coordination for 2.8-4.4x speed improvements Memory Integration: Persistent knowledge sharing across agents and sessions Quality First: Comprehensive reviews, testing, and validation Modular Design: Clean separation of concerns with clear interfaces Key Principles 1. Specification Before Code: Define requirements and constraints clearly 2. Design Before Implementation: Plan architecture and components 3. Tests Before Features: Write failing tests, then make them pass 4. Review Everything: Code quality, security, and performance checks 5. …

How to use it

Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:

@skills aiskillstore/sparc-methodology

View the source on GitHub

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