theja0473

theja0473 / automotive-claude-code-agents

Public

Automotive software engineering is one of the most complex and regulated domains in the world. Engineers juggle **ISO 26262 functional safety**, **AUTOSAR architectures**, **MISRA compliance**, **cybersecurity standards**, and **real-time embedded constraints** -- all while shipping on aggressive timelines.

19
8
100% credibility
Found Mar 22, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

An extension adding automotive engineering agents, skills, and tools to Claude Code workspaces for standards-compliant development.

How It Works

1
🔍 Discover the helper

You hear about a smart sidekick that knows everything about car engineering rules and designs.

2
👀 Preview safely

Take a quick look at what it offers without touching your setup.

3
🚀 Connect it up

With one easy action, add the automotive experts to your daily coding companion.

4
💬 Get expert advice

Chat about your safety checks or car system ideas, and receive tailored guidance right away.

5
📊 Check progress

See what's working well or tweak as your projects grow.

🎉 Build faster

Your car engineering work speeds up with pro-level insights always ready.

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Star Growth

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AI-Generated Review

What is automotive-claude-code-agents?

This Python extension slips 75+ domain-specific agents, skills, and slash commands into your Claude Code workspace, instantly arming it for automotive software engineering chaos like AUTOSAR architectures, ISO 26262 safety, and MISRA compliance. It tackles regulated pain points—cybersecurity standards, real-time embedded constraints—by generating compliant artifacts like FMEAs or SWC scaffolds via prompts like "/automotive autosar-swc-scaffold". Zero-config install keeps your setup untouched, with Docker Compose for spinning up automotive linux or github automotive grade linux testbeds.

Why is it gaining traction?

Unlike generic LLMs, it delivers production-ready automotive software architecture patterns across 14+ domains (ADAS, battery BMS, cloud fleet analytics), weaving in automotive cybersecurity github best practices and automotive software strategies 2026 foresight. Append-safe hooks and workflows cut research from hours to minutes, hooking devs tired of standards hunting in awesome automotive github lists.

Who should use this?

Automotive software engineers at Tier 1s/OEMs grinding autosar integrations, functional safety audits, or EV calibration; ADAS perception devs needing sensor fusion pipelines; cybersecurity analysts auditing ISO 21434 TARA. Ideal for automotive software testing in V-model flows or automotive software jobs chasing automotive software and electronics 2030 edges.

Verdict

Solid docs and pytest coverage make it playable, but 19 stars and 1.0% credibility score scream early days—test maturity lags big-league github automotive software repos. Grab it for automotive software development boosts if you're deep in the stack; clean uninstall means low risk.

(198 words)

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