moai-foundation-core

The TRUST 5 quality framework enforces code quality gates for AI agent development by ensuring outputs are Tested, Readable, Unified, Secured, and Trackable. It provides structured validation to maintain consistency and security across AI-driven workflows.

SPEC-First DDD methodology guides AI workflows from specification to implementation using the EARS format and ANALYZE-PRESERVE-IMPROVE cycles. It ensures structured, reliable, and maintainable development by enforcing specification-driven domain design before code generation.

Agent delegation orchestration in MoAI ADK mandates task routing through specialized agents, avoiding direct execution. This pattern manages the 200K token budget via strategic context separation and phase-specific delegation to ensure scalable AI workflows.

Token optimization for AI skills uses progressive disclosure to structure content into three tiers: Quick, Implementation, and Advanced. This manages the 200K token budget through strategic context management and phase separation, ensuring efficient knowledge transfer.

MoAI ADK modular skill systems require a scalable file structure using SKILL.md as the entry point and a modules/ directory for extended content. This organization ensures maintainable, progressive skill development without exceeding context limits.

Progressive disclosure structures AI agent knowledge transfer into three tiers—Quick, Implementation, and Advanced—to manage context windows efficiently. It prevents token budget exhaustion by strategically separating phases and revealing complexity only when needed.