English | 한국어 | 中文 | 日本語 | Español
Codingbuddy orchestrates 35 AI agents to deliver human-expert-team-level code quality.
A single AI can't be an expert at everything. Codingbuddy creates an AI development team—architects, developers, security specialists, accessibility experts, and more—that collaborate to review, verify, and refine your code until it meets professional standards.
When you ask an AI to write code, you get a single perspective. No security review. No accessibility check. No architecture validation. Just one AI doing everything "okay" but nothing excellently.
Human development teams have specialists:
- Architects who design systems
- Security engineers who find vulnerabilities
- QA specialists who catch edge cases
- Performance experts who optimize bottlenecks
Codingbuddy brings the specialist team model to AI coding.
Instead of one AI trying to do everything, Codingbuddy coordinates multiple specialized agents that collaborate:
┌─────────────────────────────────────────────────────────────┐
│ Your Request │
│ "Implement user authentication" │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ 📋 PLAN: Solution Architect + Architecture Specialist │
│ → Design system architecture │
│ → Define security requirements │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ 🚀 ACT: Backend Developer + Test Strategy Specialist │
│ → Implement with TDD │
│ → Follow quality standards │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ 🔍 EVAL: Code Reviewer + Parallel Specialists │
│ 🔒 Security → JWT vulnerabilities? │
│ ♿ Accessibility → WCAG compliance? │
│ ⚡ Performance → Optimization needed? │
│ 📏 Quality → SOLID principles? │
└─────────────────────────────────────────────────────────────┘
│
┌─────────────┴─────────────┐
│ │
Critical > 0? Critical = 0 AND
High > 0? High = 0
│ │
▼ ▼
Return to PLAN ✅ Quality Achieved
with improvements Ship with confidence
| Tier | Agents | Role |
|---|---|---|
| Mode Agents (4) | plan-mode, act-mode, eval-mode, auto-mode | Workflow orchestration |
| Primary Agents (16) | solution-architect, technical-planner, frontend-developer, backend-developer, +12 more | Core implementation |
| Specialist Agents (15) | security, accessibility, performance, test-strategy, +11 more | Domain expertise |
When you request a feature, agents automatically collaborate:
🤖 solution-architect → Designs the approach
└── 👤 architecture-specialist → Validates layer boundaries
└── 👤 test-strategy-specialist → Plans test coverage
🤖 backend-developer → Implements the code
└── 👤 security-specialist → Reviews auth patterns
└── 👤 event-architecture → Designs message flows
🤖 code-reviewer → Evaluates quality
└── 👤 4 specialists in parallel → Multi-dimensional review
Codingbuddy enforces a quality-driven development cycle:
- PLAN: Design before coding (architecture, test strategy)
- ACT: Implement with TDD and quality standards
- EVAL: Multi-specialist review (security, performance, accessibility, quality)
- Iterate: Continue until quality targets met
# Just describe what you want
AUTO: Implement JWT authentication with refresh tokens
# Codingbuddy automatically:
# → Plans the implementation
# → Writes code following TDD
# → Reviews with 4+ specialists
# → Iterates until: Critical=0 AND High=0
# → Delivers production-ready code| Severity | Must Fix Before Ship |
|---|---|
| 🔴 Critical | Yes - Immediate security/data issues |
| 🟠 High | Yes - Significant problems |
| 🟡 Medium | Optional - Technical debt |
| 🟢 Low | Optional - Enhancement |
| Traditional AI Coding | Codingbuddy |
|---|---|
| Single AI perspective | 35 specialist agent perspectives |
| "Generate and hope" | Plan → Implement → Verify |
| No quality gates | Critical=0, High=0 required |
| Manual review needed | Automated multi-dimensional review |
| Inconsistent quality | Iterative refinement until standards met |
- Node.js 18.x or higher
- npm 9.x+ or yarn 4.x+
- A supported AI tool (Claude Code, Cursor, GitHub Copilot, etc.)
# Initialize your project
npx codingbuddy init
# Add to Claude Desktop config
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": {
"codingbuddy": {
"command": "npx",
"args": ["codingbuddy", "mcp"]
}
}
}PLAN: Implement user registration with email verification
→ AI team plans the architecture
ACT
→ AI team implements with TDD
EVAL
→ AI team reviews from 8+ perspectives
AUTO: Build a complete auth system
→ AI team iterates until quality achieved
For enhanced integration with Claude Code:
# Add the marketplace
claude marketplace add JeremyDev87/codingbuddy
# Install the plugin
claude plugin install codingbuddy@jeremydev87
# Install MCP server for full functionality
npm install -g codingbuddy| Documentation | Description |
|---|---|
| Plugin Setup Guide | Installation and configuration |
| Quick Reference | Commands and modes at a glance |
| Architecture | How plugin and MCP work together |
Codingbuddy includes a built-in terminal UI that displays real-time agent activity, task progress, and workflow state alongside your AI assistant.
# Launch MCP server with TUI auto-enabled
npx codingbuddy mcp --tui| Panel | Description |
|---|---|
| FlowMap | Visual pipeline showing active agents, stages, and progress |
| FocusedAgent | Live view of the currently active agent with sparkline activity |
| Checklist | Task completion tracking from PLAN/ACT/EVAL context |
| Activity Chart | Real-time tool invocation bar chart |
| Multi-session | Multiple Claude Code sessions share a single TUI window |
| Tool | Status |
|---|---|
| Claude Code | ✅ Full MCP + Plugin |
| Cursor | ✅ Supported |
| GitHub Copilot | ✅ Supported |
| Antigravity | ✅ Supported |
| Amazon Q | ✅ Supported |
| Kiro | ✅ Supported |
| OpenCode | ✅ Supported |
Configure the default AI model in codingbuddy.config.json:
{
"ai": {
"defaultModel": "claude-sonnet-4-20250514"
}
}| Model | Best For |
|---|---|
claude-opus-4-* |
Complex architecture, deep analysis |
claude-sonnet-4-* |
General development (default) |
claude-haiku-3-5-* |
Quick lookups (not recommended for coding) |
Optimize token usage with verbosity levels:
{
"verbosity": "compact"
}| Level | Use Case |
|---|---|
minimal |
Maximum token savings, essential info only |
compact |
Balanced, reduced formatting (default) |
standard |
Full formatting, structured responses |
detailed |
Extended explanations, examples included |
| Document | Description |
|---|---|
| Getting Started | Installation and quick setup |
| Philosophy | Vision and design principles |
| Agent System | Complete agent reference |
| Skills Library | Reusable workflow skills (TDD, debugging, PR, etc.) |
| Supported Tools | AI tool integration guides |
| Configuration | Config file options |
| API Reference | MCP server capabilities |
We welcome contributions! See CONTRIBUTING.md for guidelines.
MIT © Codingbuddy