Jetson Print Bsp Info logo

Jetson Print Bsp Info

Organization
NVIDIA-AI-IOT
jetson-print-bsp-info

Use when you need to print Jetson BSP info (L4T version, board configs, rootfs state) from a Linux_for_Tegra root on the host PC. This is an example skill.

Overview

PublisherNVIDIA-AI-IOT
Repositoryjetson-bsp-skills
Skill namejetson-print-bsp-info
Stars
73
Forks
13
Bundled files
4
LicenseApache-2.0
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.

  • 4 bundled files

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

  • Open source

    Published by NVIDIA-AI-IOT on GitHub. Read the source before you install it.

Installation

Install the Jetson Print Bsp Info 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/NVIDIA-AI-IOT/jetson-bsp-skills/tree/main/skills/jetson-print-bsp-info
  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/NVIDIA-AI-IOT/jetson-bsp-skills.git /tmp/jetson-bsp-skills
mkdir -p .claude/skills
cp -r /tmp/jetson-bsp-skills/skills/jetson-print-bsp-info .claude/skills/jetson-print-bsp-info
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jetson Print Bsp Info 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 Jetson Print Bsp Info 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 Jetson Print Bsp Info 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.

jetson-print-bsp-info

Prints a concise summary of a Jetson Linux_for_Tegra (BSP) tree on the host PC.

This skill is intended as a reference example for the jetson-bsp-skills repo and the NVIDIA-wide skills CI. It performs read-only inspection — no flashing, no rootfs changes.

Purpose

Capture a baseline snapshot of a Linux_for_Tegra BSP tree (release, board configs, rootfs state) before flashing, so issues like "wrong L4T version" or "rootfs never populated" are caught early.

When to use

  • A user has unpacked a Jetson BSP tarball and wants to confirm the L4T version, supported boards, and rootfs state before flashing.
  • You need a quick sanity check that a Linux_for_Tegra/ directory looks valid (expected scripts and config files present).

Prerequisites

  • Running on the host PC (Linux), not on the Jetson target.
  • A Linux_for_Tegra/ directory extracted from a Jetson BSP tarball.
  • Standard CLIs available: ls, head, cat, paste, sed.

Inputs

  • L4T_ROOT (optional): absolute path to the Linux_for_Tegra/ directory. If unset, use the current working directory.

Instructions

Run each step in order and print the captured values into the report shown under Output format.

  1. Resolve L4T_ROOT and validate the directory is a Linux_for_Tegra root — exit early otherwise. flash.sh and nv_tegra/ are the two anchor artifacts that every BSP ships:
    bash
    L4T_ROOT="${L4T_ROOT:-$PWD}"
    if [ ! -f "$L4T_ROOT/flash.sh" ] || [ ! -d "$L4T_ROOT/nv_tegra" ]; then
      echo "Not a Linux_for_Tegra root: '$L4T_ROOT' (missing flash.sh or nv_tegra/)"
      exit 1
    fi
    echo "$L4T_ROOT"
  2. Extract the L4T release header line. The canonical host-side location is nv_tegra/nv_tegra_release; the same file is copied into the rootfs by apply_binaries.sh. Only the first line is useful — the rest is a long list of library SHAs:
    bash
    head -1 "$L4T_ROOT/nv_tegra/nv_tegra_release" 2>/dev/null \
      || head -1 "$L4T_ROOT/rootfs/etc/nv_tegra_release" 2>/dev/null \
      || echo "L4T release info not found"
  3. List supported board config files and join them onto one comma-separated line:
    bash
    (cd "$L4T_ROOT" && ls *.conf 2>/dev/null) | paste -sd, -
  4. Check whether the rootfs has been populated. An empty rootfs/ means apply_binaries.sh has not been run yet:
    bash
    if [ -f "$L4T_ROOT/rootfs/etc/passwd" ]; then
      echo "populated"
    else
      echo "empty"
    fi

Output format

Print a short report with these sections, one line each where possible:

text
L4T root:        <path>
L4T release:     <release header line>
Board configs:   <comma-separated list>
Rootfs:          populated | empty

Examples

Example output on an Orin AGX BSP (L4T R36):

text
L4T root:        $HOME/Linux_for_Tegra
L4T release:     # R36 (release), REVISION: 3.0
Board configs:   jetson-agx-orin-devkit.conf,jetson-orin-nano-devkit.conf
Rootfs:          populated

Example output on a freshly untarred BSP where apply_binaries.sh has not been run yet:

text
L4T root:        /tmp/Linux_for_Tegra
L4T release:     # R39 (release), REVISION: 0.0
Board configs:   jetson-agx-thor-devkit.conf
Rootfs:          empty

Error handling

Each command falls back to a clearly labeled "... not found" string if the underlying file is missing — the skill never errors out mid-report. If L4T_ROOT does not contain flash.sh and nv_tegra/, exit early with a clear "not a Linux_for_Tegra root" message rather than printing misleading info.

Limitations

  • Read-only inspection only — does not validate signatures, kernel images, or device-tree overlays.
  • Only checks the presence of rootfs/etc/passwd as a populated-rootfs proxy; will not detect a half-populated rootfs.
  • Lists all *.conf board configs in L4T_ROOT/; does not try to infer which one the user intends to flash.

Troubleshooting

  • Error: Not a Linux_for_Tegra root: '...' (missing flash.sh or nv_tegra/) Cause: L4T_ROOT points at a parent directory, an extracted rootfs, or an unrelated path. Solution: Point L4T_ROOT at the directory that contains flash.sh (typically Linux_for_Tegra/).

  • Error: L4T release info not found Cause: Neither nv_tegra/nv_tegra_release nor rootfs/etc/nv_tegra_release exists — the BSP tarball may be incomplete or apply_binaries.sh was never run. Solution: Re-extract the BSP tarball or run apply_binaries.sh to populate the rootfs.

Notes

  • Do not modify any files. This skill is read-only.
  • If multiple board config files exist, list all of them — do not try to guess which one the user intends to flash.

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 Jetson Print Bsp Info AI skill do?

Use when you need to print Jetson BSP info (L4T version, board configs, rootfs state) from a Linux_for_Tegra root on the host PC. This is an example skill.

Why use Jetson Print Bsp Info on TypingMind?

Because you install it once and use it with any model. Jetson Print Bsp Info 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 Jetson Print Bsp Info in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NVIDIA-AI-IOT/jetson-bsp-skills/tree/main/skills/jetson-print-bsp-info. 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 Jetson Print Bsp Info?

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 Jetson Print Bsp Info?

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

Is the Jetson Print Bsp Info AI skill free?

Yes. It is published on GitHub by NVIDIA-AI-IOT under the Apache-2.0 license. 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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