What is the SWARM SDLC system?

SWARM is a systematic workflow for AI-assisted development that uses structured directories for backlogs, retrospectives, and knowledge management to improve AI efficiency.

Does initializing SWARM affect my existing code?

No, it primarily creates a .swarm directory for management files and updates your .gitignore. It does not modify your application source code.

What are the 'Definition of Ready' and 'Definition of Done' files?

These are YAML-based quality gates that instruct the AI on exactly what requirements must be met before starting a task and what criteria define a successful completion.

How do I use SWARM after running the init skill?

After initialization, you can typically use related commands like /swarm:ideate to create development stories or /swarm:run to execute the SDLC pipeline.

SWARM SDLC Initializer

Name: SWARM SDLC Initializer
Author: hgeldenhuys

byhgeldenhuys

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Collaboration Tools

Initializes the SWARM SDLC framework to manage AI-driven development workflows, project backlogs, and agent memory.

The SWARM SDLC Initializer is a foundational skill designed to bootstrap a structured Software Development Life Cycle (SDLC) environment specifically for AI-assisted projects. It automates the setup of the SWARM framework, creating a comprehensive directory structure that includes story backlogs, quality gates (Definition of Ready and Done), and dedicated tactical memory for AI agents. This skill is essential for developers who want to move beyond simple chat-based coding toward a systematic, repeatable process where Claude can track progress, learn from retrospectives, and maintain project-specific knowledge.

Key Features

01Updates .gitignore with necessary SWARM operational rules

02Configures AI-specific quality gates (Definition of Ready/Done)

03Sets up templates for stories, retrospectives, and knowledge items

040 GitHub stars

05Automated creation of the .swarm project management directory

06Initializes per-agent tactical memory for localized learning

Use Cases

01Standardizing AI workflow management across different development teams

02Enabling persistent agent memory and knowledge extraction for complex codebases

03Bootstrapping a new repository with an AI-native project management structure

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add hgeldenhuys/recursive-ai init

For use in Claude.ai and ChatGPT

Download Skill