Jetson Customize Pinmux logo

Jetson Customize Pinmux

Organization
NVIDIA-AI-IOT
jetson-customize-pinmux

Per-pin SFIO / direction / initial-state configurator for a Jetson Orin or Thor custom carrier from the pinmux XLSM. Do NOT use for kernel-DT overlay or ODMDATA edits.

Overview

PublisherNVIDIA-AI-IOT
Repositoryjetson-bsp-skills
Skill namejetson-customize-pinmux
Stars
73
Forks
13
Bundled files
10
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.

  • 10 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 Customize Pinmux 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-customize-pinmux
  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-customize-pinmux .claude/skills/jetson-customize-pinmux
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jetson Customize Pinmux 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 Customize Pinmux 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 Customize Pinmux 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.

Customize pinmux (per-pin SFIO / direction / state)

Overview

The Tegra pinmux spreadsheet (.xlsm) is the ground truth for every CVM ball: SoC pin name, supported SFIOs, customer-selected function, direction, and initial state. This skill parses that XLSM, runs a per-pin Q1–Q6 interactive loop, and emits the three BCT DTSIs (pinmux, gpio, padvoltage) in one shot into the overlay tracker at <source.root_path>/Linux_for_Tegra/bootloader/.

Unlike sibling skills jetson-customize-uphy / jetson-customize-pcie / jetson-customize-camera, pinmux has no kernel-DT overlay surface and no ODMDATA edit. The XLSM is the source of truth; the three emitted DTSIs land at flash time via the carrier conf's PINMUX_CONFIG= / GPIOINT_CONFIG= / PMC_CONFIG= references (which /jetson-derive-carrier set up).

Pad classification (silicon-fixed): only BD* and BI* pads have configurable pull / drive / open-drain attributes. LP5XA_*, UPHYDS_*, DP_SINGLE_*, BDMIPI16X_*, BDUSB2_*, OSCI27_* are fixed-function and skip Q4–Q6 (configurable: no).

The bundled scripts/modify_pinmux.py is the workhorse: it parses the XLSM via openpyxl>=3.1, builds the per-carrier pinmap JSON, captures pin edits into a session shim, and (on generate) writes the three DTSIs.

When to invoke

  • The user says "configure pin", "set SFIO", "edit pinmux DTSI", "set pin direction", "set initial state", or asks to repurpose a CVM ball (e.g. flip a pin between GPIO and a peripheral function).
  • A sibling skill (jetson-customize-camera, jetson-customize-pcie, jetson-customize-usb, jetson-customize-mgbe) reports an HSIO pin mismatch via pin_verifier.py and the user wants to fix it.
  • The user pre-derived a custom carrier with /jetson-derive-carrier and now wants to author the pinmux from a freshly-edited .xlsm.

Prerequisites:

  • Active profile selected (target-platform/active_target.yml → <profile>.yaml with reference_devkit: AND custom_carrier:).
  • <source.root_path>/Linux_for_Tegra/ exists as a git repo (/jetson-init-source).
  • /jetson-derive-carrier has run — the three pinmux-side BCT DTSIs (PINMUX_CONFIG, GPIOINT_CONFIG, PMC_CONFIG references in the carrier conf) exist in the overlay tracker.
  • A pinmux .xlsm is registered in the active profile at documents.custom_carrier_pinmux_xls (preferred when custom-carrier- specific) or documents.ref_devkit_pinmux_xls (fallback). The bundled modify_pinmux.py requires openpyxl>=3.1.

Procedure

See references/procedure.md for the full step-by-step procedure (Steps 1–8). Summary:

  1. Resolve active target + XLSM. Validate active profile, custom_carrier:, overlay-tracker prerequisites; resolve the pinmux .xlsm path from documents.custom_carrier_pinmux_xls → documents.ref_devkit_pinmux_xls → single XLSM under documents.root_path → user prompt.
  2. Probe. Run modify_pinmux.py probe to parse the XLSM into the per-skill scratch <KB>/pinmap/<custom-carrier>.json plus session.json shim.
  3. Lookup. Resolve a free-form user query (CVM ball, Verilog name, signal, DT pin) via modify_pinmux.py lookup; surface supported SFIO list, defaults, and configurable: yes/no.
  4. Set-pin (HARD GATE — Q1–Q6 via AskUserQuestion). Q1–Q3 (sfio / direction / initial_state) always asked; Q4–Q6 (pull / drive_type / open_drain) only when configurable: yes. tristate and e_input are derived from direction, never asked.
  5. Generate. modify_pinmux.py generate --out-dir <source.root_path>/Linux_for_Tegra/bootloader/ (root, not bootloader/generic/BCT/ — derive-carrier .dts forks live there, do not colocate). Emits: tegra<soc>-mb1-bct-{pinmux,gpio,padvoltage}-<carrier-key>.dtsi. <carrier-key> comes from the carrier conf's PINMUX_CONFIG= reference, NOT the kebab-cased carrier name.
  6. Commit (single batched commit per workflow rule). All three DTSIs are one logical edit → one customization commit. Run the commit-preview gate before each commit.
  7. Run-state sidecar + session shim. Write the user-facing <profile-stem>.jetson-customize-pinmux.json sidecar and the transient session.json shim under <workspace>/target-platform/.
  8. Summary. Emit the standard one-line + table summary.

Gotchas

  • No kernel-DT overlay; no OVERLAY_DTB_FILE edit; no render_conf.py hand-off. This skill ends at the three BCT DTSIs — the carrier conf already references them via PINMUX_CONFIG= / GPIOINT_CONFIG= / PMC_CONFIG= (set up by /jetson-derive-carrier).
  • Re-point the .dts wrapper's #include after generate. /jetson-derive-carrier forks the .dts wrappers at bootloader/generic/BCT/, but their #include lines may still pull the upstream devkit .dtsi (e.g. …-p3834-xxxx-p4071-0000.dtsi). After generate writes the new <CARRIER_KEY>.dtsi to bootloader/ root, edit each wrapper's #include to the new filename — by bare basename (#include "tegra<soc>-mb1-bct-pinmux-<CARRIER_KEY>.dtsi"), not ../../… filesystem-relative. The BCT build's cpp -I bootloader/ resolves bare basenames; that's the convention every other BCT include in the tree follows. Roll the wrapper edits into the same customization commit as the three DTSIs. See references/procedure.md Step 5 ("Sanity-check the carrier .dts wrapper").
  • Q4–Q6 gated on configurable: yes. Asking pull / drive_type / open_drain on a fixed-function pad (LP5XA_*, UPHYDS_*, BDMIPI16X_*, etc.) is silently dropped by the script and confuses the user. lookup prints configurable: yes/no — always check it before prompting Q4–Q6.
  • tristate and e_input are derived, never asked. unused → tristate=ENABLE; input / bidirectional → enable-input=ENABLE. Exposing them as separate prompts produces inconsistent DTSIs.
  • sfio=gpio requires a parseable gpio=GPIOn_PD.NN entry in the pinmap row's sfio list. Pins without one are GPIO-incapable silicon; set-pin rejects the call. Surface the rejection — don't silently fall back to a non-GPIO SFIO.
  • Marker idempotency. Every per-pin edit carries // custom-bsp: pinmux on the closing brace; gpio default-state entries carry the same marker as a trailing comment. Re-running generate must detect and update — never duplicate.
  • modify_pinmux.py is unchanged from the original framework — it reads its own session.json shim under --kb-dir. The shim is regenerated each run from the active profile + the user-facing sidecar. Do not hand-edit the shim; it's transient.
  • Multiple pinmux DTSI variants per Thor module SKU. Some carrier pins live in a different DTSI variant than the one the carrier conf references. modify_pinmux.py commit (legacy patch-in-place flow) tolerates missing per-pin blocks via pinmux.warnings[] rather than failing. Surface the warning; point at the alternate DTSI variant.
  • Don't touch the upstream BSP at <bsp_image.root_path>. All edits land in <source.root_path>/Linux_for_Tegra/bootloader/ under the pristine + customization commit pattern.

Available Scripts

ScriptPurposeArguments
scripts/modify_pinmux.pyXLSM parser + per-pin DTSI generator. Invoked via run_script() from Steps 3-6 with the subcommand of the current phase.probe | lookup | set-pin | apply | generate | commit [...] (see --help)
scripts/generate_dtsi.pyRenders pinmux/GPIO/padvoltage DTSI fragments from the bundled session state. Called by modify_pinmux.py generate.--session <path> --out-dir <dir>

Invoke from the skill body as a subprocess via run_script():

bash
# run_script: probe the carrier pinmux XLSM and write a session state
scripts/modify_pinmux.py probe --xlsm carrier.xlsm --session .pinmux-session.json

# run_script: render DTSI fragments from the final session state
scripts/modify_pinmux.py generate --session .pinmux-session.json --out-dir bsp_sources/pinmux/

References

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 Customize Pinmux AI skill do?

Per-pin SFIO / direction / initial-state configurator for a Jetson Orin or Thor custom carrier from the pinmux XLSM. Do NOT use for kernel-DT overlay or ODMDATA edits.

Why use Jetson Customize Pinmux on TypingMind?

Because you install it once and use it with any model. Jetson Customize Pinmux 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 Customize Pinmux 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-customize-pinmux. 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 Customize Pinmux?

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 Customize Pinmux?

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

Is the Jetson Customize Pinmux 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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