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modu-ai/moai-adk

MoAI-ADK

MoAI-ADK

Agentic Development Kit for Claude Code

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Go Release License: Copyleft-3.0

Official Documentation


📚 Official Documentation | GitHub Discussions


"The purpose of vibe coding is not rapid productivity but code quality."

MoAI-ADK is a high-performance AI development environment for Claude Code. 28 specialized AI agents and 52 skills collaborate to produce quality code. It automatically applies the Hybrid methodology (TDD + DDD) for new projects and DDD for existing projects, and supports dual execution modes with Sub-Agent and Agent Teams.

A single binary written in Go -- runs instantly on any platform with zero dependencies.


Why MoAI-ADK?

We completely rewrote the Python-based MoAI-ADK (~73,000 lines) in Go.

Aspect Python Edition Go Edition
Distribution pip + venv + dependencies Single binary, zero dependencies
Startup time ~800ms interpreter boot ~5ms native execution
Concurrency asyncio / threading Native goroutines
Type safety Runtime (mypy optional) Compile-time enforced
Cross-platform Python runtime required Prebuilt binaries (macOS, Linux, Windows)
Hook execution Shell wrapper + Python Compiled binary, JSON protocol

Key Numbers

  • 34,220 lines of Go code, 32 packages
  • 85-100% test coverage
  • 28 specialized AI agents + 52 skills
  • 18 programming languages supported
  • 14 Claude Code hook events

System Requirements

Platform Supported Environments Notes
macOS Terminal, iTerm2 Fully supported
Linux Bash, Zsh Fully supported
Windows WSL (recommended), PowerShell 7.x+ Native cmd.exe is not supported

Prerequisites:

  • Git must be installed on all platforms
  • Windows users: Git for Windows is required (includes Git Bash)
    • Use WSL (Windows Subsystem for Linux) for the best experience
    • PowerShell 7.x or later is supported as an alternative
    • Legacy Windows PowerShell 5.x and cmd.exe are not supported

Quick Start

1. Installation

macOS / Linux / WSL

curl -fsSL https://raw.githubusercontent.com/modu-ai/moai-adk/main/install.sh | bash

Windows (PowerShell 7.x+)

Recommended: Use WSL with the Linux installation command above for the best experience.

irm https://raw.githubusercontent.com/modu-ai/moai-adk/main/install.ps1 | iex

Requires Git for Windows to be installed first.

Build from Source (Go 1.25+)

git clone https://github.com/modu-ai/moai-adk.git
cd moai-adk && make build

Prebuilt binaries are available on the Releases page.

2. Initialize a Project

moai init my-project

An interactive wizard auto-detects your language, framework, and methodology, then generates Claude Code integration files.

3. Start Developing with Claude Code

# After launching Claude Code
/moai project                            # Generate project docs (product.md, structure.md, tech.md)
/moai plan "Add user authentication"     # Create a SPEC document
/moai run SPEC-AUTH-001                   # DDD/TDD implementation
/moai sync SPEC-AUTH-001                  # Sync docs & create PR
graph LR
    A["🔍 /moai project"] --> B["📋 /moai plan"]
    B -->|"SPEC Document"| C["🔨 /moai run"]
    C -->|"Implementation Complete"| D["📄 /moai sync"]
    D -->|"PR Created"| E["✅ Done"]
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MoAI Development Methodology

MoAI-ADK automatically selects the optimal development methodology based on your project's state.

flowchart TD
    A["🔍 Project Analysis"] --> B{"New Project?"}
    B -->|"Yes"| C["Hybrid (TDD + DDD)"]
    B -->|"No"| D{"Test Coverage ≥ 50%?"}
    D -->|"Yes"| C
    D -->|"No"| E["DDD"]
    C --> F["New Code → TDD"]
    C --> G["Existing Code → DDD"]
    E --> H["ANALYZE → PRESERVE → IMPROVE"]

    style C fill:#4CAF50,color:#fff
    style E fill:#2196F3,color:#fff
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Hybrid Methodology (Default for New Projects)

The recommended methodology for new projects and ongoing development. It automatically applies TDD or DDD depending on the type of code being modified.

Code Type Methodology Cycle Description
New code TDD RED → GREEN → REFACTOR Write tests first, make them pass, then refactor
Existing code DDD ANALYZE → PRESERVE → IMPROVE Analyze existing behavior, preserve with characterization tests, then improve incrementally

DDD Methodology (Existing Projects)

A methodology for safely refactoring existing projects with low test coverage.

ANALYZE   → Analyze existing code and dependencies, identify domain boundaries
PRESERVE  → Write characterization tests, capture current behavior snapshots
IMPROVE   → Improve incrementally under test protection

The methodology is automatically selected during moai init and can be changed via development_mode in .moai/config/sections/quality.yaml.


AI Agent Orchestration

MoAI is a strategic orchestrator. Rather than writing code directly, it delegates tasks to 28 specialized agents.

graph LR
    U["👤 User Request"] --> M["🗿 MoAI Orchestrator"]

    M --> MG["📋 Manager (8)"]
    M --> EX["⚡ Expert (9)"]
    M --> BL["🔧 Builder (3)"]
    M --> TM["👥 Team (8)"]

    MG --> MG1["spec · ddd · tdd · docs<br/>quality · project · strategy · git"]
    EX --> EX1["backend · frontend · security · devops<br/>performance · debug · testing · refactoring · chrome-ext"]
    BL --> BL1["agent · skill · plugin"]
    TM --> TM1["researcher · analyst · architect · designer<br/>backend-dev · frontend-dev · tester · quality"]

    style M fill:#FF6B35,color:#fff
    style MG fill:#4CAF50,color:#fff
    style EX fill:#2196F3,color:#fff
    style BL fill:#9C27B0,color:#fff
    style TM fill:#FF9800,color:#fff
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Agent Categories

Category Count Agents Role
Manager 8 spec, ddd, tdd, docs, quality, project, strategy, git Workflow coordination, SPEC creation, quality management
Expert 9 backend, frontend, security, devops, performance, debug, testing, refactoring, chrome-extension Domain-specific implementation, analysis, optimization
Builder 3 agent, skill, plugin Creating new MoAI components
Team 8 researcher, analyst, architect, designer, backend-dev, frontend-dev, tester, quality Parallel team-based development

52 Skills (Progressive Disclosure)

Managed through a 3-level progressive disclosure system for token efficiency:

Category Count Examples
Foundation 5 core, claude, philosopher, quality, context
Workflow 11 spec, project, ddd, tdd, testing, worktree, thinking...
Domain 5 backend, frontend, database, uiux, data-formats
Language 18 Go, Python, TypeScript, Rust, Java, Kotlin, Swift, C++...
Platform 9 Vercel, Supabase, Firebase, Auth0, Clerk, Railway...
Library 3 shadcn, nextra, mermaid
Tool 2 ast-grep, svg
Specialist 11 Figma, Flutter, Chrome Extension, Pencil...

Model Policy (Token Optimization)

MoAI-ADK assigns optimal AI models to each of 28 agents based on your Claude Code subscription plan. This maximizes quality within your plan's rate limits.

Policy Plan Opus Sonnet Haiku Best For
High Max $200/mo 23 1 4 Maximum quality, highest throughput
Medium Max $100/mo 4 19 5 Balanced quality and cost
Low Plus $20/mo 0 12 16 Budget-friendly, no Opus access

Why does this matter? The Plus $20 plan does not include Opus access. Setting Low ensures all agents use only Sonnet and Haiku, preventing rate limit errors. Higher plans benefit from Opus on critical agents (security, strategy, architecture) while using Sonnet/Haiku for routine tasks.

Configuration

# During project initialization
moai init my-project          # Interactive wizard includes model policy selection

# Reconfigure existing project
moai update -c                # Re-runs the configuration wizard

Default policy is High. After running moai update, a notice guides you to configure this setting via moai update -c.


Dual Execution Modes

MoAI-ADK provides both Sub-Agent and Agent Teams execution modes supported by Claude Code.

graph TD
    A["🗿 MoAI Orchestrator"] --> B{"Select Execution Mode"}
    B -->|"--solo"| C["Sub-Agent Mode"]
    B -->|"--team"| D["Agent Teams Mode"]
    B -->|"Default (Auto)"| E["Auto Selection"]

    C --> F["Sequential Expert Delegation<br/>Task() → Expert Agent"]
    D --> G["Parallel Team Collaboration<br/>TeamCreate → SendMessage"]
    E -->|"High Complexity"| D
    E -->|"Low Complexity"| C

    style C fill:#2196F3,color:#fff
    style D fill:#FF9800,color:#fff
    style E fill:#4CAF50,color:#fff
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Agent Teams Mode (Default)

MoAI-ADK automatically analyzes project complexity and selects the optimal execution mode:

Condition Selected Mode Reason
3+ domains Agent Teams Multi-domain coordination
10+ affected files Agent Teams Large-scale changes
Complexity score 7+ Agent Teams High complexity
Otherwise Sub-Agent Simple, predictable workflow

Agent Teams Mode uses parallel team-based development:

  • Multiple agents work simultaneously, collaborating through a shared task list
  • Real-time coordination via TeamCreate, SendMessage, and TaskList
  • Best suited for large-scale feature development and multi-domain tasks
/moai plan "large feature"          # Auto: researcher + analyst + architect in parallel
/moai run SPEC-XXX                  # Auto: backend-dev + frontend-dev + tester in parallel
/moai run SPEC-XXX --team           # Force Agent Teams mode

Sub-Agent Mode (--solo)

A sequential agent delegation approach using Claude Code's Task() API.

  • Delegates a task to a single specialized agent and receives the result
  • Progresses step by step: Manager → Expert → Quality
  • Best suited for simple and predictable workflows
/moai run SPEC-AUTH-001 --solo      # Force Sub-Agent mode

MoAI Workflow

Plan → Run → Sync Pipeline

MoAI's core workflow consists of three phases:

graph TB
    subgraph Plan ["📋 Plan Phase"]
        P1["Explore Codebase"] --> P2["Analyze Requirements"]
        P2 --> P3["Generate SPEC Document (EARS Format)"]
    end

    subgraph Run ["🔨 Run Phase"]
        R1["Analyze SPEC & Create Execution Plan"] --> R2["DDD/TDD Implementation"]
        R2 --> R3["TRUST 5 Quality Validation"]
    end

    subgraph Sync ["📄 Sync Phase"]
        S1["Generate Documentation"] --> S2["Update README/CHANGELOG"]
        S2 --> S3["Create Pull Request"]
    end

    Plan --> Run
    Run --> Sync

    style Plan fill:#E3F2FD,stroke:#1565C0
    style Run fill:#E8F5E9,stroke:#2E7D32
    style Sync fill:#FFF3E0,stroke:#E65100
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Autonomous Development Loop (Ralph Engine)

An autonomous error-fixing engine that combines LSP diagnostics with AST-grep:

/moai fix       # Single pass: scan → classify → fix → verify
/moai loop      # Iterative fix: repeats until completion marker detected (max 100 iterations)

How the Ralph Engine works:

  1. Parallel Scan: Runs LSP diagnostics + AST-grep + linters simultaneously
  2. Auto-Classification: Classifies errors from Level 1 (auto-fix) to Level 4 (user intervention)
  3. Convergence Detection: Applies alternative strategies when the same error repeats
  4. Completion Criteria: 0 errors, 0 type errors, 85%+ coverage

TRUST 5 Quality Framework

Every code change is validated against five quality criteria:

Criterion Meaning Validation
Tested Tested 85%+ coverage, characterization tests, unit tests passing
Readable Readable Clear naming conventions, consistent code style, 0 lint errors
Unified Unified Consistent formatting, import ordering, project structure adherence
Secured Secured OWASP compliance, input validation, 0 security warnings
Trackable Trackable Conventional commits, issue references, structured logging

CLI Commands

Command Description
moai init Interactive project setup (auto-detects language/framework/methodology)
moai doctor System health diagnosis and environment verification
moai status Project status summary including Git branch, quality metrics, etc.
moai update Update to the latest version (with automatic rollback support)
moai update --check Check for updates without installing
moai update --project Sync project templates only
moai worktree new <name> Create a new Git worktree (parallel branch development)
moai worktree list List active worktrees
moai worktree switch <name> Switch to a worktree
moai worktree sync Sync with upstream
moai worktree remove <name> Remove a worktree
moai worktree clean Clean up stale worktrees
moai worktree go <name> Navigate to worktree directory in current shell
moai hook <event> Claude Code hook dispatcher
moai version Display version, commit hash, and build date

Architecture

moai-adk/
├── cmd/moai/             # Application entry point
├── internal/             # Core private packages
│   ├── astgrep/          # AST-grep integration for structural code analysis
│   ├── cli/              # Cobra CLI command definitions
│   ├── config/           # Thread-safe YAML configuration management
│   ├── core/
│   │   ├── git/          # Git operations (branches, worktrees, conflict detection)
│   │   ├── project/      # Project initialization, language/framework detection
│   │   └── quality/      # TRUST 5 quality gates, parallel validators
│   ├── defs/             # Language definitions and framework detection
│   ├── git/              # Git convention validation engine
│   ├── hook/             # Compiled hook system (14 events, JSON protocol)
│   ├── loop/             # Ralph feedback loop (state machine, convergence detection)
│   ├── lsp/              # LSP client (16+ languages, parallel server management)
│   ├── manifest/         # File provenance tracking (SHA-256 integrity)
│   ├── merge/            # 3-way merge engine (6 strategies)
│   ├── rank/             # MoAI Rank sync and transcript management
│   ├── resilience/       # Retry policies and circuit breakers
│   ├── shell/            # Shell integration (worktree navigation)
│   ├── statusline/       # Claude Code status line integration
│   ├── template/         # Template deployment (go:embed), settings generation
│   ├── ui/               # Interactive TUI (selectors, checkboxes, wizards)
│   └── update/           # Binary self-update mechanism
├── pkg/                  # Public library packages
│   ├── models/           # Shared data models
│   └── version/          # Build version metadata
└── Makefile              # Build automation

Key Package Coverage

Package Purpose Coverage
foundation EARS patterns, TRUST 5, 18 language definitions 98.4%
core/quality Parallel validators, phase gates 96.8%
ui Interactive TUI components 96.8%
config Thread-safe YAML configuration 94.1%
loop Ralph feedback loop, convergence detection 92.7%
cli Cobra commands 92.0%
ralph Convergence decision engine 100%
statusline Claude Code status line 100%

Sponsors

z.ai GLM 5

MoAI-ADK partners with z.ai GLM 5 to provide a cost-effective AI development environment.

Benefit Description
70% cost savings Equivalent performance at 1/7 the price of Claude
Full compatibility Works with Claude Code with no code changes
Unlimited usage No daily/weekly token limits

Sign up for GLM 5 (extra 10% discount) -- Referral rewards are used to fund MoAI open-source development.


Frequently Asked Questions

Q: How do I customize which statusline segments are displayed?

The statusline supports 4 display presets plus custom configuration:

  • Full (default): All 8 segments displayed
  • Compact: Model + Context + Git Status + Branch only
  • Minimal: Model + Context only
  • Custom: Pick individual segments

Configure during moai init / moai update -c wizard, or edit .moai/config/sections/statusline.yaml:

statusline:
  preset: compact  # or full, minimal, custom
  segments:
    model: true
    context: true
    output_style: false
    directory: false
    git_status: true
    claude_version: false
    moai_version: false
    git_branch: true

See SPEC-STATUSLINE-001 for details.


Q: What does the version indicator in statusline mean?

The MoAI statusline shows version information with update notifications:

🗿 v2.2.2 ⬆️ v2.2.5
  • v2.2.2: Currently installed version
  • ⬆️ v2.2.5: New version available for update

When you're on the latest version, only the version number is displayed:

🗿 v2.2.5

To update: Run moai update and the update notification will disappear.

Note: This is different from Claude Code's built-in version indicator (🔅 v2.1.38). The MoAI indicator tracks MoAI-ADK versions, while Claude Code shows its own version separately.


Q: "Allow external CLAUDE.md file imports?" warning appears

When opening a project, Claude Code may show a security prompt about external file imports:

External imports:
  /Users/<user>/.moai/config/sections/quality.yaml
  /Users/<user>/.moai/config/sections/user.yaml
  /Users/<user>/.moai/config/sections/language.yaml

Recommended action: Select "No, disable external imports"

Why?

  • Your project's .moai/config/sections/ already contains these files
  • Project-specific settings take precedence over global settings
  • The essential configuration is already embedded in CLAUDE.md text
  • Disabling external imports is more secure and doesn't affect functionality

What are these files?

  • quality.yaml: TRUST 5 framework and development methodology settings
  • language.yaml: Language preferences (conversation, comments, commits)
  • user.yaml: User name (optional, for Co-Authored-By attribution)

Contributing

Contributions are welcome! See CONTRIBUTING.md for detailed guidelines.

Quick Start

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/my-feature
  3. Write tests (TDD for new code, characterization tests for existing code)
  4. Ensure all tests pass: make test
  5. Ensure linting passes: make lint
  6. Format code: make fmt
  7. Commit with conventional commit messages
  8. Open a pull request

Code quality requirements: 85%+ coverage · 0 lint errors · 0 type errors · Conventional commits

Community


Star History

Star History Chart


License

Copyleft 3.0 -- See the LICENSE file for details.

Links