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Nhtsa Vehicle

Community
jgsystemsconsulting
nhtsa-vehicle

Synthesized reference notes from three US Government vehicle-safety sources: NHTSA Cybersecurity Best Practices for the Safety of Modern Vehicles (updated 2022, final), NHTSA Automated Driving Systems 2.0: A Vision for Safety (2017), and a 16-section selection of 49 CFR Part 571 (FMVSS) pinned at eCFR versioner date 2025-01-01. Use for voluntary vehicle cybersecurity practices, the ADS 2.0 twelve priority safety design elements, and FMVSS occupant protection, brakes/stability/lighting, and fuel/EV integrity requirements. Not ISO 26262, not ASPICE, not ISO/SAE 21434, not UNECE R155/R156, not SAE J3016, and not the full Part 571; the FMVSS material is a selection of vehicle-level minimum performance standards, not a process standard.

Overview

Publisherjgsystemsconsulting
Repositoryjgs-se-knowledge-packs
Skill namenhtsa-vehicle
Stars
121
Forks
1
Bundled files
7
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by jgsystemsconsulting on GitHub. Read the source before you install it.

Installation

Install the Nhtsa Vehicle AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/jgsystemsconsulting/jgs-se-knowledge-packs/tree/main/packs/nhtsa-vehicle
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jgsystemsconsulting/jgs-se-knowledge-packs.git /tmp/jgs-se-knowledge-packs
mkdir -p .claude/skills
cp -r /tmp/jgs-se-knowledge-packs/packs/nhtsa-vehicle .claude/skills/nhtsa-vehicle
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nhtsa Vehicle in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Nhtsa Vehicle on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Nhtsa Vehicle is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

NHTSA Vehicle Safety

Source: NHTSA (US Department of Transportation) | Chapters: 6

When to use

Use this skill when work touches modern road vehicles in the United States and you need what NHTSA actually publishes: the voluntary 2022 cybersecurity best practices for vehicle makers and their suppliers, the ADS 2.0 safety-design elements for automated driving systems, or the selected FMVSS performance requirements for occupant protection, brakes, stability, lighting, fuel integrity, and electric-vehicle shock protection. It is a synthesized reference for engineers who need the shape and content of these sources quickly, with the pinned FMVSS date stated up front.

Prerequisites: none. Plain Markdown; no MCP server, API key, or licence tier needed at runtime.

How to Use This Skill

  • Without arguments: read the core frameworks below (the cyber guidance's practice structure, the ADS 2.0 twelve priority safety design elements, and the FMVSS selection as vehicle-level minimum performance standards).
  • With a topic: ask about a practice or requirement directly, e.g. "OTA update security", "operational design domain", "FMVSS 208 occupant crash protection", "EV electrolyte spillage and shock protection".
  • With a chapter number: ch02 (cybersecurity practices), ch03 (ADS safety vision), ch04 through ch06 (the FMVSS selection by hazard group).

Core Frameworks & Mental Models

Voluntary Cybersecurity Best Practices (2022 Guidance)

NHTSA's 2022 document is non-binding, voluntary guidance organized as a risk-based practice structure, not a management-system standard and not a checklist with pass/fail criteria. Its own structure:

  • General best practices: leadership priority on product cybersecurity; a risk-based approach tied to the vehicle development process; information sharing across the industry; a security vulnerability reporting program; an organizational incident-response process; and self-auditing of cybersecurity processes.
  • Aftermarket and serviceability: practices for aftermarket devices and diagnostic service access.
  • Technical best practices: controlled developer and debugging access on production devices; cryptographic techniques and credential management; vehicle diagnostic functionality; event logs and fleet trend review; protection of wireless paths into the vehicle; and software update processes, including over-the-air updates.

The framing to keep: cybersecurity weaknesses can become safety problems, so the guidance treats the vehicle as a cyber-physical system and encourages each organization to decide how to apply the practices.

ADS 2.0: Twelve Priority Safety Design Elements

Automated Driving Systems 2.0: A Vision for Safety (2017) is voluntary guidance for SAE J3016 Level 3 through 5 ADS. Its core framework is twelve priority safety design elements an entity designing an ADS should address:

  1. System safety
  2. Operational Design Domain (ODD)
  3. Object and Event Detection and Response (OEDR)
  4. Fallback (Minimal Risk Condition)
  5. Validation methods
  6. Human Machine Interface (HMI)
  7. Vehicle cybersecurity
  8. Crashworthiness
  9. Post-crash ADS behavior
  10. Data recording
  11. Consumer education and training
  12. Federal, State, and local laws

Around the elements, the document introduces the Voluntary Safety Self-Assessment (VSA) as the entity-produced public artifact, and guidance for States on distinguishing vehicle performance (NHTSA's lane) from licensing and operation (the States' lane). See ch03 for the currency caveat before relying on this as current federal ADS policy.

FMVSS: Vehicle-Level Minimum Performance Standards

The FMVSS material is a 16-section selection of 49 CFR Part 571, pinned at eCFR versioner date 2025-01-01. FMVSS are minimum performance requirements for the vehicle (or specified equipment): each states what must be achieved under defined applications and test conditions. They are not process standards, not software assurance schemes, and not hazard-analysis methods. The selection groups by hazard:

  • Occupant protection (ch04): interior impact (201), occupant crash protection (208), seat belt assemblies (209), seat belt assembly anchorages (210), side impact protection (214), ejection mitigation (226).
  • Brakes, stability, and lighting (ch05): transmission shift position/braking effect (102), windshield defrosting and defogging (103), hydraulic and electric brake systems (105), lighting and reflective devices (108), electronic stability control (126), automatic emergency braking (127), light-vehicle brake systems (135).
  • Fuel integrity, EV, and minimum sound (ch06): fuel system integrity (301), electric-powered vehicle electrolyte spillage and electrical shock protection (305), quiet-vehicle minimum sound (141).

Chapter Index

ChapterSectionKey content
ch01IntroductionWhat the pack is, the three sources, the pinned date, what it refuses
ch02Cybersecurity practicesSynthesized notes from the 2022 final guidance
ch03ADS safety visionSynthesized notes from ADS 2.0, with the currency caveat
ch04Occupant protectionFMVSS 201, 208, 209, 210, 214, 226
ch05Brakes, stability, lightingFMVSS 102, 103, 105, 108, 126, 127, 135
ch06Fuel integrity and EVFMVSS 301, 305, and 141 (minimum sound for hybrid and electric vehicles)

Topic Index

  • ADS safety vision (twelve priority safety design elements, VSA) → ch03
  • Aftermarket devices and serviceability → ch02
  • Automatic emergency braking (FMVSS 127) → ch05
  • Brake systems (FMVSS 105, 135) → ch05
  • Crashworthiness and post-crash ADS behavior → ch03
  • Cybersecurity practices (voluntary, 2022 guidance) → ch02
  • Data recording for ADS → ch03
  • Electronic stability control (FMVSS 126) → ch05
  • EV electrical shock protection (FMVSS 305) → ch06
  • Fuel system integrity (FMVSS 301) → ch06
  • Incident response and vulnerability reporting (vehicle makers) → ch02
  • Lighting and reflective devices (FMVSS 108) → ch05
  • Minimum sound for hybrid and electric vehicles (FMVSS 141) → ch06
  • Occupant crash protection (FMVSS 208) → ch04
  • Operational Design Domain (ODD) and OEDR → ch03
  • Over-the-air and software updates → ch02
  • Seat belt assemblies and anchorages (FMVSS 209, 210) → ch04
  • Side impact protection and ejection mitigation (FMVSS 214, 226) → ch04
  • Transmission shift position and braking effect (FMVSS 102) → ch05
  • Windshield defrosting and defogging (FMVSS 103) → ch05

Supporting Files

None. No glossary, no patterns, no cheatsheet. The pack spec makes these optional and this pack does not need them: the chapters carry the reference content and the Topic Index above routes to them.

Scope & Limits

Covers: the three sources named above, at their stated versions. The cyber material is NHTSA's 2022 final guidance and is guidance, not a regulation and not a mandate: it imposes no obligation and has no conformity scheme. The ADS 2.0 material carries a currency caveat: current as of the 2026-09-25 vetting check per docs/SOURCE-VETTING.md post-v1.21.0 row (FR action of 2026-07-31); a successor exists in draft; do not treat ADS 2.0 as final federal ADS policy.

FMVSS: this pack is a 16-section selection, not all of Part 571. The FMVSS are vehicle-level minimum performance standards, not a process standard: they say what the vehicle must achieve under test, not how to organize engineering work to get there. The selection omits most of Part 571's other bands, including school bus, motorcycle, and heavy-truck specific standards; make no completeness claim for those vehicle classes.

Not covered, and where to look instead:

  • Functional safety per ISO 26262: see the functional-safety-signpost skill.
  • Automotive process capability per ASPICE and cybersecurity engineering per ISO/SAE 21434: see the automotive-signpost skill.
  • Type-approval cybersecurity regulation per UNECE R155/R156: see the automotive-signpost skill.
  • SAE driving-automation level definitions per SAE J3016: ADS 2.0 references the levels but this pack does not reproduce the standard; see the automotive-signpost skill.

Third-party material: the NHTSA sources cite ISO, SAE, and UNECE standards by name. This pack names them and reproduces none of their text; pages carrying verbatim third-party standard text were dropped at build time (see PACK.yaml). The FMVSS text is US Government public domain; the pack restates and synthesizes it rather than reprinting section text.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Nhtsa Vehicle AI skill do?

Synthesized reference notes from three US Government vehicle-safety sources: NHTSA Cybersecurity Best Practices for the Safety of Modern Vehicles (updated 2022, final), NHTSA Automated Driving Systems 2.0: A Vision for Safety (2017), and a 16-section selection of 49 CFR Part 571 (FMVSS) pinned at eCFR versioner date 2025-01-01. Use for voluntary vehicle cybersecurity practices, the ADS 2.0 twelve priority safety design elements, and FMVSS occupant protection, brakes/stability/lighting, and fuel/EV integrity requirements. Not ISO 26262, not ASPICE, not ISO/SAE 21434, not UNECE R155/R156, not...

Why use Nhtsa Vehicle on TypingMind?

Because you install it once and use it with any model. Nhtsa Vehicle is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Nhtsa Vehicle in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jgsystemsconsulting/jgs-se-knowledge-packs/tree/main/packs/nhtsa-vehicle. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Nhtsa Vehicle?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Nhtsa Vehicle?

As many as you like. As long as a model supports skills, you can use Nhtsa Vehicle with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Nhtsa Vehicle AI skill free?

It is published on GitHub by jgsystemsconsulting. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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