moai-foundation-core

MoAI Foundation Core serves as the architectural backbone for the MoAI-ADK ecosystem, providing a standardized set of principles and patterns for AI-driven development. It is designed for engineers and developers looking to implement high-quality, scalable agentic workflows. By enforcing rigorous standards, the framework ensures that autonomous agents function reliably, securely, and within defined token constraints while maximizing output quality. The core focus is on replacing direct, unstructured execution with structured, multi-agent orchestration, facilitating maintainability in complex software development life cycles.

• TRUST 5 Quality Framework: Implements a systematic approach to quality assurance through Test-first, Readable, Unified, Secured, and Trackable pillars with automated validation gates.

• SPEC-First TDD: A formal development methodology that prioritizes requirement specifications before implementation, utilizing the EARS format to minimize token waste during the planning phase.

• Delegation Patterns: Orchestrates task execution through specialized agents, utilizing sequential, parallel, and conditional execution strategies to prevent monolithic agent behavior.

• Token Budgeting: Advanced context management techniques, including strategic /clear commands and modular file loading, designed to optimize the 200K token budget for maximum efficiency.

• Progressive Disclosure: A multi-tier knowledge architecture that delivers information based on implementation depth, supporting onboarding and advanced configuration.

• Modular Architecture: Promotes system scalability via file splitting and standardized reference architectures, ensuring that complex workflows remain manageable.

• Typical inputs include development requirements, technical specifications, and task prompts; outputs are highly structured, tested code units and documentation sets.

• The framework is optimized for scenarios involving large-scale AI automation, complex codebase refactoring, and automated skill generation.

• Key performance indicators include test coverage (>85%), token utilization efficiency, and adherence to security constraints defined in execution rules.

• Practical constraints involve adhering to the defined agent catalog and strictly following the /moai-based command reference to maintain system consistency.

• Use the provided TOON-based workflow templates for seamless integration with ADB-enabled hardware and device control environments.