Ethan-YS

Ethan-YS / project-brain

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One folder. Every session knows where you left off. — An open-source methodology for AI-assisted projects.

ai-assistant ai-coding ai-pair-programming claude-code context-management
10
0
100% credibility
Found May 06, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Shell
AI Summary

project-brain is a folder structure and set of guidelines designed to help AI coding assistants maintain and share project context across sessions and collaborators.

How It Works

1
🔍 Discover project-brain

You hear about a simple way to help your AI assistant remember your project details across different chats or team members, so it never starts from scratch.

2
Choose your setup
⭐
Quick AI skill install

Tell your favorite AI helper to set it up automatically if it supports skills.

📋
Manual folder copy

Copy the ready-made memory folder into your project with one easy command.

3
✏️ Fill in your project story

Add a quick summary of what your project is, what's next, and key decisions to the memory files.

4
🧠 AI reads the memory

Open a new chat with your AI assistant, and it instantly knows the full project status from just a few key notes.

5
🔄 Switch sessions smoothly

Jump to a new window or share with a friend – the AI picks up right where you left off.

6
🩺 Check project health

Run a quick scan to spot any outdated notes or missing details.

🎉 Seamless teamwork

Your AI collaborator stays sharp and productive, saving time and frustration on every project.

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Star Growth

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AI-Generated Review

What is project-brain?

Project-brain sets up a single-folder structure in your repo to give AI coding assistants like Claude Code, Cursor, or Copilot instant project continuity across sessions, windows, or collaborators. It solves the chaos of scattered docs and lost context in long AI-assisted projects—where even huge context windows fail without smart organization—using Shell scripts for one-click scaffolding and health checks, plus git-based protocols for handoffs. You get a methodology where every new session reads minimal files to ramp up fast, like a one folder app with deep meaning for AI workflows.

Why is it gaining traction?

Unlike generic doc templates or bloated READMEs, it enforces volatility-based separation (stable overviews vs. session notes) and decision logs capturing rejected alternatives, making AI handoffs reliable without token waste. The hook is dead-simple setup—scaffold your project in one command, pick adapters for your tools—and a doctor script flagging doc rot like overgrown status files. It nods to brain simulation efforts like blue brain project github or human brain project github, but for practical dev pacing.

Who should use this?

AI power users on Cursor or Claude Code building sustained projects, like indie devs iterating SaaS prototypes or teams juggling ops and dev streams. Perfect for those tired of re-explaining status every terminal session—one folder up linux or back in cmd suddenly feels structured.

Verdict

Try it if you're deep in AI coding; the methodology shines for continuity, with solid docs and examples despite 10 stars and 1.0% credibility score. Still early—battle-tested on few projects—so scaffold a side gig first to validate.

(198 words)

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