AI-DLC stands for AI-Driven Development Life Cycle, a specialized framework designed to optimize collaboration between developers and AI models through structured documentation and lifecycle stages.

How does it handle existing projects?

If the skill detects existing source code, it marks the project as 'Brownfield' and suggests running reverse engineering to help the AI understand the current architecture.

Does this skill overwrite my existing source code?

No, the skill only creates a new directory called aidlc-docs to store lifecycle state and documentation. It analyzes existing code but does not modify it during the start phase.

What happens if I try to start a project that is already initialized?

The skill will detect the existing aidlc-state.md file, inform you that the project is already active, and recommend using the resume command instead to prevent state conflicts.

Why are questions asked in Markdown files instead of chat?

By using [Answer] tags in .md files, the skill ensures that all project context and decisions are permanently documented and easily accessible to both the AI and human developers.

AI-DLC Workflow Starter

Name: AI-DLC Workflow Starter
Author: yamatatsu

byyamatatsu

0•

Productivity & Workflow

Initializes and orchestrates the AI-Driven Development Life Cycle (AI-DLC) by analyzing your workspace and establishing a structured documentation environment.

The AI-DLC Workflow Starter is the essential entry point for the AI-Driven Development Life Cycle framework, designed to bridge the gap between AI agents and professional software engineering practices. It performs comprehensive workspace detection to determine if a project is greenfield or brownfield, then automatically generates a standardized directory structure and state files. By enforcing a documentation-first approach where all project inquiries are handled via Markdown files rather than ephemeral chat, it ensures a persistent, audit-ready, and highly organized development process from day one.

Key Features

01Guided workflow transitions to requirements gathering or reverse engineering

02Automated workspace detection for greenfield and brownfield project categorization

03Documentation-first interaction model to prevent lost context in chat sessions

04Standardized initialization of the aidlc-docs directory structure

05Persistent state management via aidlc-state.md and audit logging

060 GitHub stars

Use Cases

01Standardizing software development lifecycles across a team using Claude Code

02Onboarding an AI agent to an existing codebase to perform maintenance or feature additions

03Starting a new software project with a structured, AI-assisted architecture and documentation plan

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add yamatatsu/claude-aidlc start

For use in Claude.ai and ChatGPT

Download Skill