LeoKemp223

LeoKemp223 / NextBoard

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面向硬件产品PCB方案设计的AI Agent，Agent会自动帮你进行需求确认，实时分析国内外各类芯片技术方案，进行器件选型，下载datasheet，输出BOM表，计算价格，输出模块原理图，最终整合成可落地技术方案。

agent-skills agentic-ai autonomous-agents bom chip
17
0
100% credibility
Found May 05, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

NextBoard is an AI skill that guides hardware design by taking product requirements and producing structured PCB schematics, BOMs, cost estimates, and validated plans.

How It Works

1
🔍 Discover NextBoard

You hear about NextBoard, a smart helper that turns your hardware ideas into ready-to-build circuit plans.

2
📥 Add the Helper

You easily add NextBoard to your AI design workspace so it's ready to assist with electronics projects.

3
🔄 Refresh Your Space

You refresh your AI workspace to wake up the new helper and see it in your list of tools.

4
💡 Describe Your Idea

You simply tell it what you want to build, like a drone controller or word-learning card, and it starts the magic.

5
⚙️ Watch It Design

The helper confirms your needs, compares chip options from around the world, selects parts, draws circuits, and lists costs.

6
✅ Review the Plan

It double-checks everything for risks, completeness, and buildability, giving clear scores before finalizing.

🎉 Get Your Blueprint

You receive a full package with diagrams, parts lists, datasheets, and a polished PDF scheme ready to hand off to makers.

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Star Growth

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AI-Generated Review

What is NextBoard?

NextBoard is a Python-based AI agent for automating PCB schematic design in hardware products. Feed it natural language requirements like "design a drone controller" and it runs a 7-stage workflow: confirms specs, compares chip architectures (domestic, international, hybrid), selects components, pulls datasheets, generates BOMs with pricing, draws module schematics, and packages everything into review-ready Markdown, PDFs, and libraries. Developers get landing-ready tech proposals without manual research.

Why is it gaining traction?

It stands out with built-in quality gates, independent reviewer agents scoring completeness/risks/costs, and supply chain risk checks favoring Chinese alternatives—rare in generic AI tools. The hook is instant, structured outputs for complex hardware decisions, plus seamless integration into Claude Code, Codex, or Cursor via $hardware-solution command. NextBoard AI skips the nextboard logistics or nextboard ngv boilerplate, delivering pro-grade docs fast.

Who should use this?

Embedded hardware engineers prototyping IoT devices, motor controllers, or e-ink gadgets. Teams scouting nextboard ngv-compatible chips or domestic suppliers for cost/risk audits. Python devs in hardware firms needing quick feasibility studies before full CAD.

Verdict

With 17 stars and 1.0% credibility score, NextBoard feels early-stage but punches above via polished docs, installer scripts, and validation tests—install and experiment if you're in hardware prototyping. Skip for production until more battle-tested.

(198 words)

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