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startproject

Orchestrate multi-agent AI planning to create an approved project plan.

Updated Nov 9, 2025
Search Tags:#design#research#codebase analysis#agent teams#project kickoff#ai planning
One-click install
npx skills add https://github.com/ribon-org/ribon --skill startproject-ribon-org
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: startproject
Source: https://github.com/ribon-org/ribon/tree/main/.claude/skills/startproject
Command: npx skills add https://github.com/ribon-org/ribon --skill startproject-ribon-org

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the initial planning phase of a new project or feature by leveraging AI for codebase understanding, parallel research, and design synthesis, ensuring a solid foundation before implementation.

Core Features & Use Cases

  • Codebase Analysis: Understand existing codebases using large context models (Gemini 1M).
  • Parallel Research & Design: Utilize AI agent teams (Researcher, Architect) for concurrent investigation and architectural planning.
  • Plan Synthesis & Approval: Consolidate AI findings into a clear project brief and implementation plan for user approval.
  • Use Case: Kickstart a new feature by having AI analyze the current project structure, research necessary libraries, design the architecture, and present a detailed plan for your review.

Quick Start

Initiate a new project plan for the 'user-authentication' feature.

Frequently Asked Questions about startproject

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I use AI planning to kickstart a new project feature?▼

AI kickoff planning uses multi-agent collaboration to analyze your codebase, conduct parallel research, and synthesize findings into an implementation plan for your review. It streamlines the initial phase before any code is written.

Can AI agents research libraries and design architecture concurrently?▼

Yes, specialized AI agent teams like Researcher and Architect conduct concurrent investigation and architectural planning. This parallel research and design process ensures comprehensive exploration of necessary libraries and structural design for your project.

What is the best way to analyze an existing codebase before implementation?▼

Codebase analysis using large context models like Gemini 1M is the best way to understand existing project structures. It allows the AI to process extensive code, providing a solid foundation for architectural planning and feature integration.

Does AI project planning require manual approval before implementation?▼

Yes, AI project planning requires manual approval. The system consolidates its research and design findings into a clear project brief and implementation plan, which you must review and approve before moving forward with the actual development.

When do I need multi-agent collaboration for software engineering?▼

You need multi-agent collaboration for software engineering when kicking off a new project or feature that requires deep codebase understanding and strategic planning. It is ideal for synthesizing complex research and design tasks into a unified plan.

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