Official agent skill

Jetson Derive Carrier

by NVIDIA in NVIDIA/skills

Bootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit.

OfficialApache-2.0Auto-check passedAI & LLM Engineering

Install Jetson Derive Carrier

skills CLI
$ npx skills add NVIDIA/skills --skill jetson-derive-carrier -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NVIDIA/skills jetson-derive-carrier --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/jetson-derive-carrier .claude/skills/jetson-derive-carrier && rm -rf skills-src

Use ~/.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/

Facts

Skill name
jetson-derive-carrier
GitHub stars
3.5k
Token cost
~4.2k tokens
SKILL.md length
1,798 words
Files
5
Skills in repo
386
Repo updated
First seen
Licence
Apache-2.0

At a glance

Bootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit.

  • Tasks that involve GPU and accelerator computing
  • SKILL.md covers Instructions, Examples, Purpose and Prerequisites, plus 2 more sections
  • Calls git
  • Tasks that involve Project scaffolding

What it does

Jetson Derive Carrier is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Bootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit. Use after jetson-init-source; not for module-level or kernel-DTB changes.

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `BENCHMARK.md`, `evals/evals.json` and `skill-card.md`).

It sits in AI & LLM Engineering, covering GPU and accelerator computing and Project scaffolding. 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.

When your agent uses it

  • Tasks that involve GPU and accelerator computing
  • Tasks that involve Project scaffolding

Example prompts

  • “/jetson-derive-carrier”

What it can do on your machine

Read from SKILL.md and the folder at commit dfdd080. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Jetson Derive Carrier loads about 4.2k tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 1,798 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~52
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k

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.

Safety

Auto-check passed

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from NVIDIA/skills at commit dfdd080, republished under its Apache-2.0 licence (© NVIDIA). 1,798 words, ~4,216 tokens.

Download SKILL.mdSave it as .claude/skills/jetson-derive-carrier/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
jetson-derive-carrier
description
Bootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit. Use after jetson-init-source; not for module-level or kernel-DTB changes.
version
0.0.1
license
Apache-2.0
metadata.data-classification
public
metadata.author
Jetson Team
metadata.tags
target-platform, custom-carrier, bring-up, setup
metadata.domain
meta

jetson-derive-carrier

Customize first-run gate for any customize-* skill on a custom carrier. Resolve the active target per target-platform-contract.md. Refuse if no custom_carrier: block, or if <source.root_path>/Linux_for_Tegra/.git is missing (jetson-init-source first). Template file create/copy rows land in a single overlay-tracker commit and copy directly to the custom-carrier-renamed target path — reference-named pristine files are never staged (see Fork plan for the local rule, which overrides the standard pristine + customization split from the workflow); conf-chain discovery follows per-board conf dispatch. Kernel base DTB is not forked — carrier deltas layer as a DT overlay wired via OVERLAY_DTB_FILE.

Identifiers (from active profile): <chip> from reference_devkit.module.id via catalogue (unknown → warn, fallback tegra234); <module-id>/<module-sku> from reference_devkit.module; <carrier-id>/<carrier-sku> from reference_devkit.carrier; <custom-id>/<custom-sku>/ <custom-flash-conf> from custom_carrier. <real-conf> = readlink <bsp_image.root_path>/Linux_for_Tegra/<reference_devkit.flash_config> (NVIDIA convention <devkit>.conf → <carrier>-<module>-a<rev>.conf; warn + treat top-level as real + skip symlink-wrapper row if not a symlink).

<custom-id> is a custom carrier board token, not necessarily an NVIDIA-style pNNNN ID. Use it verbatim in dash-form filenames and DT compatible strings. When a target file family uses p-stripped numeric tokens, derive <custom-id-file-token> as NNNN only if <custom-id> matches ^p[0-9]{4}$; otherwise use <custom-id> unchanged. Do not reject custom carrier IDs merely because they do not start with p.

Instructions

The fork plan below is the instruction set: one discovery pass, then a row-by-row fork of the per-board fileset, gated by the commit-message preview before each git commit.

Fork plan

Every git commit produced by this skill — in the overlay tracker (Linux_for_Tegra/) or the hardware/ source repo — runs through the commit message preview gate. Surface the staged file list + proposed message to the operator and require accept / edit / cancel before each git commit; on cancel leave the index staged for manual resolution.

Materialize renamed forks even when bytes do not change. For every accepted fork-plan row, create and track the custom-carrier target path; do not skip a missing target because the fork is only a rename/copy or is byte-identical to the reference. This includes BCT forks such as pinmux, GPIO/GPIOINT, padvoltage/PMC, misc, and MB2 misc. Skip only when the Acceptance column allows it, the source is an explicit warn-and-skip miss, or the expected target path is already tracked; in the last case, report it as already derived and do not create an empty commit.

Template file create/copy rows squash into one overlay-tracker commit, and reference-named pristine files are never staged. All rows that materialize a new (template-derived) file in the overlay tracker — board flash-conf, flash-conf symlink, MB1 BCT (pinmux, GPIO/GPIOINT, padvoltage/PMC, misc), MB2 BCT (misc), BPMP DTB (when opted in), nvpmodel, nvfancontrol — copy directly from <bsp_image.root_path>/Linux_for_Tegra/<rel>/<reference-name> to <source.root_path>/Linux_for_Tegra/<rel>/<custom-name> with any content edits applied before staging. The reference-named (<carrier-id>-<carrier-sku>-keyed) filename is never staged or committed in the overlay tracker — only the custom-carrier-renamed file is tracked. This overrides the standard pristine + customization split from commit batching. All such rows land in a single overlay-tracker commit that adds: (i) the custom-carrier-named files at their target paths with content already applied, (ii) the flash-conf symlink, and (iii) the targeted flash-conf content rewrites inside the renamed flash-conf for PINMUX_CONFIG / GPIO_CONFIG / GPIOINT_CONFIG / PMC_CONFIG / MISC_CONFIG / MB2_BCT (plus BPFDTB_FILE when BPMP DTB is opted in). Rows that edit existing upstream files instead of creating templates — the nvpower.sh patch — and the overlay wire-up (OVERLAY_DTB_FILE+= append to the just-created flash-conf fork, treated as a temporally distinct phase per commit batching) remain separate commits per their own rows. The DT overlay skeleton commits in bsp_sources/hardware/, not the overlay tracker, so it is unaffected. The commit message preview gate fires once on the squashed commit; warn-and-skipped rows do not contribute, and if every row in the bundle is already tracked the commit is omitted entirely.

Discovery (single batched pass)

Run one discovery pass; do not interleave with staging. Do not truncate listings — every candidate filename in each scanned directory must be visible to the matcher. head, tail, | head -N, | tail -N, and any other row-limiting filter are out of bounds for this step; use ls -1 / find unclipped, or grep on the full output. Truncating risks false warn-and-skip calls when the matching file sits past the cutoff. Capture:

  • Flash-conf vars: DTB_FILE / TBCDTB_FILE / BPFDTB_FILE / PINMUX_CONFIG / PMC_CONFIG / GPIO_CONFIG / GPIOINT_CONFIG. DTB_FILE / TBCDTB_FILE are captured for reference only so the overlay wire-up can derive <dtb-stem> for the overlay filename — they are never rewritten by this skill.
  • BCT .dts at bootloader/generic/BCT/; .dtsi siblings live one level up at bootloader/ — NOT alongside.
  • nvpmodel: nvpmodel_<module-id>_<module-sku>*.conf. nvfancontrol: nvfancontrol_<module-id>_<module-sku>_<carrier-id>_<carrier-sku>.conf.
  • nvpower.sh anchors for (a)–(d): <carrier-id> cvb branch, <module-id>-<module-sku> SKU elif, tegra<chip> nvpmodel cascade, tegra<chip> nvfancontrol cascade.
File / categoryDiscoveryAcceptanceFork rule
Board flash conf<real-conf>AlwaysFilename sub <carrier-id>-<carrier-sku> → <custom-id>-<custom-sku>. Content sub is targeted, not blanket: rewrite RHS only for vars whose file this skill forks — PINMUX_CONFIG, PMC_CONFIG, GPIO_CONFIG / GPIOINT_CONFIG, MISC_CONFIG, MB2_BCT. Other carrier-keyed vars (DTB_FILE, TBCDTB_FILE, SCR_CONFIG, PMIC_CONFIG, DEVICEPROD_CONFIG, PROD_CONFIG, MINRATCHET_CONFIG, UPHY_CONFIG, dynamic OVERLAY_DTB_FILE+=) MUST stay at reference values — their files aren't forked here and a blanket sed would point them at nonexistent files. DTB_FILE / TBCDTB_FILE specifically: base DTB is not forked; the overlay row appends a new OVERLAY_DTB_FILE+= line instead. BPFDTB_FILE: opt-in extra commit. Never touch <chip>, <module-id>, xxxx.
Flash-conf symlinkUnconditionalAlways (skip if <real-conf> not a symlink)New symlink <custom-flash-conf> → flash-conf fork
MB1 BCT pinmuxPINMUX_CONFIG + #include follow ¶AlwaysRename rule †
MB1 BCT GPIOGPIO_CONFIG/GPIOINT_CONFIG + #include follow ¶AlwaysRename rule †
MB1 BCT padvoltagePMC_CONFIG + #include follow ¶AlwaysRename rule †
MB1 BCT miscMISC_CONFIG + #include follow ¶AlwaysRename rule †
MB2 BCT miscMB2_BCT + #include follow ¶AlwaysRename rule †
Kernel DTB + source DTS(reference only — see header)Never forkedBase DTB stays at reference. No pristine binary copy in the overlay tracker; no source DTS fork in bsp_sources/hardware/. Carrier deltas live entirely in the DT overlay (next row).
DT overlay skeleton (NEW)UnconditionalAlwaysCreate <source.root_path>/hardware/nvidia/<chip>/nv-public/overlay/<chip>-<custom-id>-<custom-sku>+<module-id>-<module-sku>.dts (skeleton ‡); commit in hardware/, push to origin
Per-dir Makefile registration<source.root_path>/bsp_sources/hardware/nvidia/<chip>/nv-public/overlay/MakefileAlwaysAppend dtbo-y += <chip>-<custom-id>-<custom-sku>+<module-id>-<module-sku>.dtbo after the last literal-named dtbo-y += entry (BEFORE the $(addprefix $(makefile-path)/,$(dtbo-y)) prefix block — inserting after dtbo-y += $(old-dtbo) silently drops the .dtbo). Same position-sensitive idiom and snippet as the composite slot's Makefile patch in ../jetson-build-source/references/composite-registration.md#makefile-patch-idempotent-position-sensitive. Commit in hardware/. Without this row, nvidia-dtbs never produces the .dtbo referenced by the next row's OVERLAY_DTB_FILE+= line and flash.sh aborts mid-flash on the missing file.
Overlay wire-upUnconditionalAlwaysAppend OVERLAY_DTB_FILE+=",<chip>-<custom-id>-<custom-sku>+<module-id>-<module-sku>.dtbo" to flash-conf fork (extra commit)
nvpmodel configrootfs/etc/nvpmodel/nvpmodel_<module-id-num>_<module-sku>.confAlwaysFilename: append _<custom-id-file-token>_<custom-sku>
nvfancontrol configrootfs/etc/nvpower/nvfancontrol/nvfancontrol_<module-id-num>_<module-sku>_<carrier-id-num>_<carrier-sku>.confAlwaysFilename: substitute carrier portion (append _<custom-id-file-token>_<custom-sku> if source is module-keyed only)
nvpower.sh patchrootfs/etc/systemd/nvpower.shAlwaysPristine + single customization commit with 4 insertions: (a) cvb cascade elif [[ "${machine}" =~ "<custom-id>" ]]; then cvb="<custom-id-file-token>" before reference; (b) inside module-SKU branch set machine="<module-id>-<module-sku>-<custom-id>-<custom-sku>"; (c) nvpmodel cascade branch for composite machine key → conf_file= nvpmodel fork; (d) cvb-keyed nvfancontrol cascade branch → conf_file= nvfancontrol fork
BPMP DTBprebuilt at bootloader/generic/<BPFDTB_FILE> (alt naming: no p prefix, xxxx SKU)Opt-in y/N, default N — module-level, usually shared with referenceFork binary: pristine + filename sub -<carrier-id-num>- → -<custom-id-file-token>- (content unchanged). Extra commit on flash-conf fork rewriting BPFDTB_FILE to the renamed binary.

#include follow. Scan each captured .dts for #include "..." directives anywhere in the file (NVIDIA BSPs put them inside BCT node bodies); carrier-keyed includes join the fork list. Stop at one level.

† Rename rule. Carrier-keyed source (e.g. …-p3834-xxxx-p4071-0000.dts) → filename sub <carrier-id>-<carrier-sku> → <custom-id>-<custom-sku>; rewrite the flash-conf variable (e.g. PINMUX_CONFIG) to the renamed filename in the same customization commit. Module portion is preserved verbatim from pristine — if pristine has p3834-xxxx, fork keeps p3834-xxxx; if pristine has p3834-0008, fork keeps p3834-0008. Never pin module-SKU on your own. Same rule for any other xxxx wildcard in the carrier-SKU position when pristine uses it (e.g. p4071-xxxx → p1234-xxxx). Module-keyed source (e.g. …-p3767-dp-a03.dtsi) → append _<custom-id-file-token>_<custom-sku> (underscore-form) or -<custom-id>-<custom-sku> (dash-form) plus an extra commit on flash-conf fork rewriting the variable (e.g. PINMUX_CONFIG) to the suffixed name. Content never substituted by default; prompt if content holds a literal carrier-id-sku self-reference.

‡ Overlay skeleton. DT plugin overlay (/plugin/;) with one fragment@0 at target-path = "/"; inside __overlay__ set model = "<custom_carrier.name> carrier board" and compatible = "nvidia,<custom-id>-<custom-sku>+<module-id>-<module-sku>", "nvidia,<chip>". nvpower.sh machine narrowing reads compatible.

Show full SKILL.md (495 more words)Show less
Edit verification

Re-grep after every sed / patch. sed silently no-ops on miss; exit code 0 proves nothing. Multi-line replacements: use Python str.replace(old, new), not multi-line sed (brittle to whitespace drift, silent no-ops). Refuse to commit on verification miss.

Summary. Print forks per repo (count + commit SHAs), BPMP-DTB decision, warn-and-skipped rows (mandatory source file missing on this BSP — don't fail the run), overlay path written.

Examples

Trigger phrases the operator might use:

text
derive custom carrier
bootstrap custom carrier
fork carrier board from reference devkit

Minimal custom_carrier: block in the active profile that the skill expects to find:

yaml
custom_carrier:
  id: p1234            # any token; need not be NVIDIA pNNNN style
  sku: 0000
  flash_config: p1234.conf
  name: Acme Custom Carrier

Purpose

Customize the per-board fileset for a new carrier board so downstream customize-* skills, nvpower.sh, and the boot chain land on the custom carrier instead of the reference devkit. Base DTB stays at the reference; carrier deltas live in a DT overlay so a re-derive against a new reference BSP only needs to re-run this skill.

Prerequisites

  • Active profile resolved per target-platform-contract.md with a custom_carrier: block (id, sku, flash-conf, friendly name).
  • source.root_path/Linux_for_Tegra/.git initialized — run /jetson-init-source first; this skill refuses if the overlay tracker is missing.
  • bsp_image.root_path populated by /jetson-init-image so the reference flash-conf symlink can be resolved.
  • reference_devkit: populated (module + carrier) so the rename rule has carrier-id/sku tokens to substitute away from.

Limitations

  • Kernel base DTB and its source DTS are not forked — carrier deltas must layer through the DT overlay wired via OVERLAY_DTB_FILE.
  • BPMP DTB fork is opt-in (default OFF). Most carrier swaps share the reference BPMP DTB; only opt in when board power/clock topology diverges.
  • Flash-conf content substitution is targeted, not blanket. Vars whose files this skill does not fork (DTB_FILE, TBCDTB_FILE, SCR_CONFIG, PMIC_CONFIG, DEVICEPROD_CONFIG, PROD_CONFIG, MINRATCHET_CONFIG, UPHY_CONFIG, dynamic OVERLAY_DTB_FILE+=) stay at reference values — rewriting them would point at files that do not exist.
  • Custom-carrier IDs need not follow NVIDIA pNNNN style; the p-stripped numeric token is derived only when the ID matches ^p[0-9]{4}$.
  • Does not customize module-level files. Use the relevant jetson-customize-* skill for pinmux, clocks, fan curves, nvpmodel, PCIe, UPHY, USB, MGBE, or camera deltas.

Troubleshooting

  • Refuses with "no custom_carrier: block" — declare the block in the active profile before re-running; the skill will not infer it.
  • Refuses with ".git missing in Linux_for_Tegra/" — overlay tracker not initialized. Run /jetson-init-source first.
  • "<real-conf> not a symlink" — NVIDIA convention is a <devkit>.conf symlink to <carrier>-<module>-a<rev>.conf; if the top-level is the real conf, the skill warns, treats it as real, and skips the symlink-wrapper row. Not an error.
  • sed reported success but the edit is missing — sed silently no-ops on miss. The skill re-greps after every patch and refuses to commit on verification miss; for multi-line replacements switch to Python str.replace.
  • "chip: unknown" / fallback to tegra234 — module ID is not in the catalogue; update the catalogue rather than override in the profile.
  • Commit message preview prompt blocks the run — expected gate per commit-batching; accept, edit, or cancel. On cancel the index is left staged for manual resolution.
  • A mandatory source file is missing on this BSP — the row is recorded as warn-and-skipped in the summary; the rest of the run still completes.

© 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

Files

SKILL.md and 4 other files in skills/jetson-derive-carrier of NVIDIA/skills.

  • SKILL.md
  • BENCHMARK.md
  • evals/evals.json
  • skill-card.md
  • skill.oms.sig

Open the folder on GitHubat commit dfdd080

Compare with similar skills

Jetson Derive Carrier 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.

Jetson Derive Carrier compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Jetson Derive Carrier this skillNVIDIA/skills3.5k—~4.2kAutomated safety check: PassApache-2.0
Fla Triton To Gluonfla-org/flash-linear-attention5.8k—~4.2kAutomated safety check: PassMIT
Megatron-LM on SLURMNVIDIA/Megatron-LM18k—~1.8kAutomated safety check: PassApache-2.0
DGX Spark Memory and Thermal Opswshobson/agents40k—~2kAutomated safety check: PassMIT
DGX Spark Training Gotchaswshobson/agents40k—~2kAutomated safety check: PassMIT
Cosmos Policy EvaluationOrchestra-Research/AI-Research-SKILLs13k—~3.7kAutomated safety check: PassMIT

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Questions about Jetson Derive Carrier

What does Jetson Derive Carrier do?

Bootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit. Jetson Derive Carrier is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Bootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit.

When should I use Jetson Derive Carrier?

Jetson Derive Carrier fits situations like: tasks that involve GPU and accelerator computing; tasks that involve Project scaffolding.

How do I install Jetson Derive Carrier in Claude Code?

Run `npx skills add NVIDIA/skills --skill jetson-derive-carrier -a claude-code`. Or copy the skill folder (skills/jetson-derive-carrier in NVIDIA/skills) into .claude/skills/jetson-derive-carrier in your project. Claude Code loads it when a task matches its description.

How do I install Jetson Derive Carrier in Codex?

Run `npx skills add NVIDIA/skills --skill jetson-derive-carrier -a codex`. Or copy the skill folder (skills/jetson-derive-carrier in NVIDIA/skills) into .agents/skills/jetson-derive-carrier in your project. Codex loads it when a task matches its description.

Can I use Jetson Derive Carrier in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill jetson-derive-carrier -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-derive-carrier, .gemini/skills/jetson-derive-carrier, .github/skills/jetson-derive-carrier and .opencode/skills/jetson-derive-carrier in your project.

What does Jetson Derive Carrier need to run?

Going by SKILL.md and its folder, Jetson Derive Carrier needs the command-line tools its instructions call (git).

Does Jetson Derive Carrier access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Jetson Derive Carrier safe to install?

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. Review the folder before installing.

What licence does Jetson Derive Carrier use?

Jetson Derive Carrier 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.

How many tokens does Jetson Derive Carrier use?

About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Jetson Derive Carrier?

Skills that share tags, products or a category with Jetson Derive Carrier: 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.

Who maintains Jetson Derive Carrier?

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.