moai-foundation-core

Define foundational workflow, quality, and delegation rules for AI-assisted software development.

Updated Feb 24, 2026
One-click install
npx skills add https://github.com/Jongsix/remote-claudecode --skill moai-foundation-core-jongsix
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: moai-foundation-core
Source: https://github.com/Jongsix/remote-claudecode/tree/main/.claude/skills/moai-foundation-core
Command: npx skills add https://github.com/Jongsix/remote-claudecode --skill moai-foundation-core-jongsix

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides the foundational operating model for MoAI-style AI development, helping teams keep quality, workflow, context, and execution rules consistent across complex coding tasks.

Core Features & Use Cases

  • Quality governance: Applies the TRUST 5 framework to enforce testing, readability, consistency, security, and traceability.
  • Workflow orchestration: Defines SPEC-First DDD phases for planning, implementation, and documentation sync.
  • Token and context management: Helps control context growth, phase boundaries, and selective loading for large tasks.
  • Agent delegation patterns: Describes sequential, parallel, and conditional delegation to specialized agents.
  • Use case: A developer can use this skill to structure a feature from requirements through tests and documentation while staying within quality and budget constraints.

Quick Start

Ask for the MoAI foundation core guidance for your task, including the relevant workflow, quality gates, and token-saving steps.

Frequently Asked Questions about moai-foundation-core

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I standardize AI-assisted software development workflows for complex coding projects?

Agent delegation patterns distribute tasks sequentially, in parallel, or conditionally to specialized agents. This modular architecture controls execution rules and maintains workflow consistency across complex coding tasks.

What is the TRUST 5 framework for quality governance in AI development?

The TRUST 5 framework enforces testing, readability, consistency, security, and traceability gates in AI development. It provides quality validation rules to ensure standardized outputs across specification-driven implementations.

How do I manage token budgets and context growth during large AI coding tasks?

Generate EARS-based SPEC documents by applying a spec-first DDD workflow. This approach defines planning and implementation phases, ensuring requirements are structured for traceability before coding begins.

How do I delegate tasks to specialized AI agents sequentially or in parallel?

Delegate tasks to specialized AI agents using sequential, parallel, or conditional delegation patterns. This modular architecture distributes workload while maintaining workflow orchestration and quality constraints.

Can I use progressive disclosure to optimize context loading for modular architecture?

Progressive disclosure optimizes context loading by selectively exposing modular architecture components only when needed. This controls token budgeting and prevents context overflow during complex software engineering tasks.

When should I not use a spec-first DDD approach for AI-assisted coding?

Spec-first DDD is less suitable for rapid prototyping or exploratory coding where requirements are undefined. It requires clear specification inputs to enforce TRUST 5 quality gates and generate EARS-based documentation effectively.