juno-agent

juno-task-ts

TypeScript implementation of juno-task CLI tool for AI subagent orchestration.

Overview

juno-task-ts is an AI-powered development CLI that orchestrates subagents (Claude, Cursor, Codex, Gemini) through MCP (Model Context Protocol) servers. It provides a modern TypeScript implementation with React INK TUI, comprehensive testing infrastructure, and automated feedback collection.

Installation

This package is available on NPM under multiple names for flexibility:

# Primary package (recommended)
npm install -g juno-agent

# Alternative installations
npm install -g juno-code
npm install -g juno-ts-task

All three packages provide the same functionality and binary commands.

Getting Started

Prerequisites

• Node.js (v18 or higher)
• Python 3.8+ (for dependency scripts)
• Git for version control
• NPM or UV package manager

Quick Start

# Initialize a new project
juno-agent init --task "Your task" --subagent claude --git-url "https://github.com/user/repo"

# Start task execution
juno-agent start

# Or use the universal command
juno --help

# Collect feedback during execution
juno-collect-feedback

Available Commands

All packages install these binary commands:

• juno - Universal command (recommended)
• juno-agent - Package-specific command
• juno-code - Package-specific command
• juno-ts-task - Legacy command
• juno-collect-feedback - Feedback collection utility

Project Structure

.
├── .juno_task/
│   ├── prompt.md          # Production-ready AI instructions
│   ├── init.md            # Task breakdown and constraints
│   ├── plan.md            # Dynamic planning and tracking
│   ├── USER_FEEDBACK.md   # User feedback and issue tracking
│   └── specs/             # Comprehensive specifications
│       ├── README.md      # Specs overview and guide
│       ├── requirements.md # Detailed functional requirements
│       └── architecture.md # System architecture and design
├── CLAUDE.md              # Session documentation and learnings
├── AGENTS.md              # AI agent selection and performance tracking
└── README.md              # This file

AI-Powered Development

This project implements a sophisticated AI development workflow:

• Task Analysis: AI studies existing codebase and requirements
• Specification Creation: Detailed specs with parallel subagents
• Implementation: AI-assisted development (up to 500 parallel agents)
• Testing: Automated testing with dedicated subagents
• Documentation: Continuous documentation updates
• Version Control: Automated Git workflow with smart commits

Key Features

• Production-Ready Templates: Comprehensive templates for AI guidance
• Parallel Processing: Up to 500 parallel subagents for analysis
• Automated Workflows: Git integration, tagging, and documentation
• Quality Enforcement: Strict requirements against placeholder implementations
• User Feedback Integration: Continuous feedback loop via USER_FEEDBACK.md
• Session Management: Detailed tracking of development sessions

Configuration

The project uses claude as the primary AI subagent with these settings:

• Parallel Agents: Up to 500 for analysis, 1 for build/test
• Quality Standards: Full implementations required
• Documentation: Comprehensive and up-to-date
• Version Control: Automated Git workflow

Development Workflow

• Review Task: Check .juno_task/init.md for main task
• Check Plan: Review .juno_task/plan.md for current priorities
• Provide Feedback: Use juno-task feedback for issues or suggestions
• Track Progress: Monitor AI development through .juno_task/prompt.md

Created with juno-task on 2025-10-08 using claude as primary AI subagent