Per-pin SFIO / direction / initial-state configurator for a Jetson Orin or Thor custom carrier from the pinmux XLSM.
$ npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills jetson-customize-pinmux --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/jetson-customize-pinmux .claude/skills/jetson-customize-pinmux && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "jetson-customize-pinmux" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-pinmux into .claude/skills/jetson-customize-pinmux/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-pinmux", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-pinmuxType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills jetson-customize-pinmux --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/jetson-customize-pinmux .agents/skills/jetson-customize-pinmux && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jetson-customize-pinmux" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-pinmux into .agents/skills/jetson-customize-pinmux/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-pinmux", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills jetson-customize-pinmux --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/jetson-customize-pinmux .cursor/skills/jetson-customize-pinmux && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "jetson-customize-pinmux" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-pinmux into .cursor/skills/jetson-customize-pinmux/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-pinmux", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA/skills.git --path skills/jetson-customize-pinmux--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills jetson-customize-pinmux --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/jetson-customize-pinmux .gemini/skills/jetson-customize-pinmux && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "jetson-customize-pinmux" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-pinmux into .gemini/skills/jetson-customize-pinmux/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-pinmux", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA/skills jetson-customize-pinmuxInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/jetson-customize-pinmux .github/skills/jetson-customize-pinmux && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "jetson-customize-pinmux" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-pinmux into .github/skills/jetson-customize-pinmux/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-pinmux", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA/skills jetson-customize-pinmux --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/jetson-customize-pinmux .opencode/skills/jetson-customize-pinmux && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "jetson-customize-pinmux" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-pinmux into .opencode/skills/jetson-customize-pinmux/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-pinmux", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
jetson-customize-pinmuxPer-pin SFIO / direction / initial-state configurator for a Jetson Orin or Thor custom carrier from the pinmux XLSM.
Jetson Customize Pinmux is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. 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.
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts and reference files (for example `BENCHMARK.md`, `evals/evals.json` and `questions.json`).
It sits in AI & LLM Engineering, covering GPU and accelerator computing. It works with NVIDIA AI Platform. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.
8 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit dfdd080. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 4 files in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
CARRIER_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Jetson Customize Pinmux loads about 2.4k tokens when it runs, and up to ~6.7k if it reads all its reference files. Until then it costs about 48 tokens; SKILL.md has 969 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from NVIDIA/skills at commit dfdd080, republished under its Apache-2.0 licence (© NVIDIA). 969 words, ~2,414 tokens.
.claude/skills/jetson-customize-pinmux/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.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.
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./jetson-derive-carrier
and now wants to author the pinmux from a freshly-edited .xlsm.Prerequisites:
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..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.See references/procedure.md for the full
step-by-step procedure (Steps 1–8). Summary:
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.modify_pinmux.py probe to parse the XLSM into the
per-skill scratch <KB>/pinmap/<custom-carrier>.json plus
session.json shim.modify_pinmux.py lookup; surface
supported SFIO list, defaults, and configurable: yes/no.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.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.<profile-stem>.jetson-customize-pinmux.json sidecar and the
transient session.json shim under
<workspace>/target-platform/.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)..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").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.// 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.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.<bsp_image.root_path>. All
edits land in <source.root_path>/Linux_for_Tegra/bootloader/ under
the pristine + customization commit pattern.| Script | Purpose | Arguments |
|---|---|---|
scripts/modify_pinmux.py | XLSM 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.py | Renders 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():
# 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/procedure.md — full Step 1–8
procedure prose.questions.json — Q1–Q6 prompt schema consumed
by Step 4.../../references/platform_template.yaml — documents: block (ref_devkit_pinmux_xls, custom_carrier_pinmux_xls).../../context/bsp-customization-workflow.md — overlay edit protocol (single-commit per DTSI fork).../jetson-derive-carrier/SKILL.md — must run first; produces the pinmux / gpio / padvoltage DTSI forks this skill edits, and rewrites the carrier conf's PINMUX_CONFIG= / GPIOINT_CONFIG= / PMC_CONFIG= lines to point at them.../jetson-init-source/SKILL.md — produces the overlay tracker this skill commits into.../jetson-link-docs/SKILL.md — author the profile's documents: block, including the pinmux XLSM bindings.© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 10 other files (scripts, references) in skills/jetson-customize-pinmux of NVIDIA/skills.
Open the folder on GitHubat commit dfdd080
Jetson Customize Pinmux next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Jetson Customize Pinmux this skillNVIDIA/skills | 3.5k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Fla Triton To Gluonfla-org/flash-linear-attention | 5.8k | — | ~4.2k | Automated safety check: Pass | MIT | |
| Megatron-LM on SLURMNVIDIA/Megatron-LM | 18k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| DGX Spark Memory and Thermal Opswshobson/agents | 40k | — | ~2k | Automated safety check: Pass | MIT | |
| DGX Spark Training Gotchaswshobson/agents | 40k | — | ~2k | Automated safety check: Pass | MIT | |
| Cosmos Policy EvaluationOrchestra-Research/AI-Research-SKILLs | 13k | — | ~3.7k | Automated safety check: Pass | MIT |
fla-org/flash-linear-attention
Workflow for porting an existing Triton kernel in fla/ops/ to Gluon (triton.experimental.gluon) to gain explicit control over tensor layouts, shared memory, async data movement (cp.async / TMA), MMA…
NVIDIA/Megatron-LM
Shows how to launch distributed Megatron-LM training on a SLURM cluster: sbatch skeleton, torch.distributed.run setup, CUDA_DEVICE_MAX_CONNECTIONS rules and failure diagnosis.
wshobson/agents
Plans memory headroom, works through out-of-memory failures and watches temperature and power during long ML training jobs on NVIDIA DGX Spark.
wshobson/agents
Preflight checks and diagnosis for ten known failure modes of ML training on NVIDIA DGX Spark's GB10, spanning launch errors, memory, thermals, bandwidth and precision.
Orchestra-Research/AI-Research-SKILLs
Sets up and runs NVIDIA Cosmos Policy evaluations on the LIBERO and RoboCasa simulators, including headless GPU rendering and inference latency profiling.
Orchestra-Research/AI-Research-SKILLs
Fine-tunes and evaluates OpenVLA-OFT and OFT+ robot policies with LoRA and continuous action heads on LIBERO simulation and ALOHA real-robot setups.
NVIDIA/skills
A skill your agent uses when the user wants to deploy, run, debug, tear down, or call the REST API of the RTVI-CV 2D detection / tracking microservice.
NVIDIA/skills
Generates, validates, compares and explains HOLOLINK_def.svh macro files for the HSB IP, using bundled Python scripts and asking before it writes anything.
NVIDIA/skills
Runs and validates an end-to-end Mission Control demo in a locally installed Isaac Sim, with a Nova Carter robot driven through a Python server.
NVIDIA/skills
Orchestrates defect image generation for PCBA, metal surface and glass inspection with NVIDIA Cosmos AnomalyGen on OSMO, from cold-start Day 0 to real-photo Day 1 labeling.
NVIDIA/skills
Orchestrates video data augmentation and auto-labeling workflows on OSMO, from flow selection and preflight checks to submission, monitoring and output download.
NVIDIA/skills
Runs NVIDIA TAO Data Services KPI analysis on object detection results, comparing predictions to ground truth and writing per-class precision, recall and AP to a CSV.
Works with
Categories
Per-pin SFIO / direction / initial-state configurator for a Jetson Orin or Thor custom carrier from the pinmux XLSM. Jetson Customize Pinmux is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Per-pin SFIO / direction / initial-state configurator for a Jetson Orin or Thor custom carrier from the pinmux XLSM.
Jetson Customize Pinmux fits situations like: kernel-DT overlay; tasks that involve GPU and accelerator computing.
Run `npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a claude-code`. Or copy the skill folder (skills/jetson-customize-pinmux in NVIDIA/skills) into .claude/skills/jetson-customize-pinmux in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a codex`. Or copy the skill folder (skills/jetson-customize-pinmux in NVIDIA/skills) into .agents/skills/jetson-customize-pinmux in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill jetson-customize-pinmux -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jetson-customize-pinmux, .gemini/skills/jetson-customize-pinmux, .github/skills/jetson-customize-pinmux and .opencode/skills/jetson-customize-pinmux in your project.
Going by SKILL.md and its folder, Jetson Customize Pinmux needs Python for the scripts in its folder and credentials named CARRIER_KEY. Our summary lists: Python 3; A credential in CARRIER_KEY.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Jetson Customize Pinmux is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.4k tokens (SKILL.md is roughly 9.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.3k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Jetson Customize Pinmux: Fla Triton To Gluon (fla-org/flash-linear-attention, 5.8k stars), Megatron-LM on SLURM (NVIDIA/Megatron-LM, 18k stars), DGX Spark Memory and Thermal Ops (wshobson/agents, 40k stars) and DGX Spark Training Gotchas (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,546 GitHub stars. The repository holds 386 skills in this directory. The repository was last updated on October 9, 2026.
Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
