russelleNVy

russelleNVy / three-man-team

Public

A structured 3-agent AI dev team — Architect, Builder, Reviewer. Built from production use. Token-optimized. Works with Claude Code, VS Code, Cursor, and any AI that supports context files.

agent-skills agent-workflow ai-agents claude context-files
16
2
100% credibility
Found Apr 01, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Shell
AI Summary

A set of templates and guides to organize AI assistants into a three-member team—Architect, Builder, and Reviewer—for more reliable and efficient coding assistance.

How It Works

1
💡 Discover the AI Team

You hear about a clever way to use AI helpers for coding by dividing tasks among three specialized roles like a real team.

2
Choose Your Setup
🌍
For All Projects

Set it up once to use the team everywhere you work.

📁
For This Project

Add the team just to the project you're starting now.

3
📦 Add Team to Project

You place the ready-made team instructions into your project's folder so everyone is on the same page.

4
🗣️ Chat with the Architect

You start a conversation with the planning leader who reviews your goals and creates a clear action plan.

5
👷 Builder Creates It

The builder follows the plan exactly, making what was asked for without extras.

6
🔍 Reviewer Checks Quality

The checker looks everything over and sends it back if it's not perfect, ensuring top quality.

🚀 Your Project Succeeds

With the team's help, your software updates go live smoothly, saving time and reducing errors.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 16 to 16 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is three-man-team?

Three-man-team sets up a structured three-agent AI dev workflow—Architect plans tasks, Builder implements briefs exactly, and Reviewer checks for issues before deploy. It tackles undisciplined AI coding tools that waste tokens on full codebases or drift off-task, enforcing handoffs and rules via context files for Claude Code, VS Code, Cursor, or any LLM supporting structured output. Built in Shell, you get a quick git clone install, project templates, and token-optimizer rules that cut redundant work.

Why is it gaining traction?

It stands out with GitHub LLM structured output baked in, drawing from DeepMind multi-agent research for three-person teams that beat solo AIs without coordination bloat—think three man team meaning real dev handoffs. Developers hook on the 30-second global setup and production-tested token savings, like parallel tool calls and no-restate rules, plus compatibility with structured output OpenAI GitHub tools or RTK for bash compression. Low-overhead process trumps vague prompts.

Who should use this?

Solo devs or small teams shipping SaaS with Claude Code who burn tokens on sloppy AI sessions. Indie hackers building structured RAG apps or using Cursor for fast prototypes. AI-coders tired of one-shot generations in VS Code needing reviewer gates.

Verdict

Try it if you're deep in LLM dev—solid docs and production roots make the 1.0% credibility score and 16 stars forgivable for an early MIT-licensed tool. Skip if you want battle-tested scale; it's raw but evolves fast.

(178 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.