ErwanLorteau

ErwanLorteau / BMAD_Openclaw

Public

Bridging the BMad Method to OpenClaw — Structured AI-driven development workflows.

ai-agents ai-orchestration bmad-method openclaw software-development
190
56
100% credibility
Found Feb 20, 2026 at 90 stars 2x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

This repository adapts the BMad Method for use with OpenClaw by providing prompts, configuration examples, and instructions to orchestrate a team of AI agents for structured software development within a single chat session.

How It Works

1
🔍 Discover the AI Team Builder

You hear about a smart way to build software using a team of AI helpers that work together from your idea to finished app.

2
📁 Add to Your AI Workspace

You place this helpful guide into the folder where your AI assistant keeps its tools and instructions.

3
✏️ Describe Your App Idea

You make a simple note with your app's name, a short description, and where to save the results.

4
📖 Teach Your AI the Method

You add easy instructions to your AI's main guidebook so it knows how to lead the team of helpers.

5
💬 Start Chatting with Your AI

You tell your AI to run the process for your app idea, and it kicks off the team right in the conversation.

6
👥 Watch the Team Collaborate

Specialized helpers pop up one by one, creating plans, designs, code, reviews, and tests while you stay in control.

🎉 Enjoy Your Finished Software

You get a complete, high-quality app ready to use, with everything checked and improved along the way.

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AI-Generated Review

What is BMAD_Openclaw?

BMAD_Openclaw bridges the BMad method to OpenClaw, letting you run a 12-agent AI dev team from a single chat session using sessions_spawn. It takes a product idea through planning—briefs, PRDs, architecture, UX specs, epics—to execution with stories, code, reviews, QA, and retrospectives, all in isolated sub-agents. Developers get production-ready artifacts like stories, code with tests, and sprint status files, slashing token costs versus CLI-heavy alternatives.

Why is it gaining traction?

This bridging stands out by enabling parallel agents, crash recovery via file-based state, and conversational orchestration—no menus or PTYs needed. Users notice responsive main sessions that halt for input, respawn blockers, and track everything in YAML configs for custom stacks like Next.js and Supabase. With 65 stars, it's hooking devs bridging BMad workflows on GitHub for efficient, low-overhead AI sprints.

Who should use this?

Indie hackers prototyping SaaS apps who want structured AI assistance without tool sprawl. Solo full-stack devs handling planning-to-ship pipelines for web projects. Teams experimenting with 12-agent setups in OpenClaw for faster iteration on epics and stories.

Verdict

Try the dev branch for a closer BMad mirror with extra agents—solid docs and setup make it accessible despite 65 stars and 1.0% credibility score signaling early maturity. Great for OpenClaw users bridging methods, but wait for more adoption if you need battle-tested stability.

(198 words)

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