What happens during the Planning stage?

The skill analyzes project context, design artifacts, and dependencies to create a detailed markdown plan. This plan must be approved by the user before any actual code generation begins.

Where is the generated code stored?

All application code is written directly to your workspace root (e.g., src/, tests/), while internal planning and audit logs are stored in the aidlc-docs directory.

Can I use this for frontend development?

Yes, the skill includes rules for UI code generation, such as automatically adding data-testid attributes to facilitate future automation and testing.

Does this skill work with existing codebases?

Yes, it features specific 'Brownfield' rules that allow it to modify existing files in-place while adhering to the established project structure and coding standards.

AI-DLC Code Generation & Planning

Name: AI-DLC Code Generation & Planning
Author: yamatatsu

byyamatatsu

0•

Developer Tools

Automates the generation of production-ready code and tests through a structured two-part planning and approval workflow.

This skill implements the 'Construction' phase of the AI Development Lifecycle (AI-DLC), focusing on transforming design artifacts into functional code units. It enforces a high-quality output by splitting the process into a detailed planning phase—where dependencies and architectural rules are analyzed—and an execution phase where the AI generates application code, tests, and deployment artifacts. Designed for both greenfield and brownfield projects, it ensures consistency by following strict file placement rules and requiring human approval before any code is written to the workspace.

Key Features

01Support for multiple environments including Node.js, Python, Rust, and Go

02Automatic generation of unit tests and deployment artifacts

03Integrated audit logging and state management via AI-DLC docs

040 GitHub stars

05Two-stage 'Planning → Generation' workflow for maximum control

06Context-aware logic for both Greenfield and Brownfield projects

Use Cases

01Refactoring existing legacy codebases using structured AI-DLC methodologies

02Generating boilerplate-free application logic with integrated unit tests and API layers

03Building new features or modules within a microservices or monolithic architecture

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add yamatatsu/claude-aidlc construction-code-generation

For use in Claude.ai and ChatGPT

Download Skill