Enable Jetson Thor 25G/10G/1G MGBE QSFP via kernel-DT overlay.
$ npx skills add NVIDIA/skills --skill jetson-customize-mgbe -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills jetson-customize-mgbe --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-mgbe .claude/skills/jetson-customize-mgbe && 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-mgbe" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-mgbe into .claude/skills/jetson-customize-mgbe/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-mgbe", 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-mgbeType 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-mgbe -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills jetson-customize-mgbe --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-mgbe .agents/skills/jetson-customize-mgbe && 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-mgbe" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-mgbe into .agents/skills/jetson-customize-mgbe/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-mgbe", 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-mgbe -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills jetson-customize-mgbe --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-mgbe .cursor/skills/jetson-customize-mgbe && 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-mgbe" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-mgbe into .cursor/skills/jetson-customize-mgbe/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-mgbe", 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-mgbe--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-mgbe -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills jetson-customize-mgbe --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-mgbe .gemini/skills/jetson-customize-mgbe && 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-mgbe" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-mgbe into .gemini/skills/jetson-customize-mgbe/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-mgbe", 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-mgbeInstalls 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-mgbe -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-mgbe .github/skills/jetson-customize-mgbe && 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-mgbe" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-mgbe into .github/skills/jetson-customize-mgbe/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-mgbe", 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-mgbe -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-mgbe --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-mgbe .opencode/skills/jetson-customize-mgbe && 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-mgbe" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-customize-mgbe into .opencode/skills/jetson-customize-mgbe/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-customize-mgbe", 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-mgbeEnable Jetson Thor 25G/10G/1G MGBE QSFP via kernel-DT overlay.
Jetson Customize Mgbe is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Enable Jetson Thor 25G/10G/1G MGBE QSFP via kernel-DT overlay. Do NOT use for UPHY lane allocation or ODMDATA edits.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files and assets (for example `BENCHMARK.md`, `assets/questions.json` and `evals/evals.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.
No scripts in the folder and no shell commands in SKILL.md.
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 no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Jetson Customize Mgbe loads about 2.1k tokens when it runs, and up to ~7k if it reads all its reference files. Until then it costs about 35 tokens; SKILL.md has 879 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); files beside SKILL.md are not scanned.
The full file from NVIDIA/skills at commit dfdd080, republished under its Apache-2.0 licence (© NVIDIA). 879 words, ~2,059 tokens.
.claude/skills/jetson-customize-mgbe/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.Thor T264 exposes mgbe0..mgbe3. On a custom carrier, the 25G QSFP cage
(or 10G / 1G fiber path) is wired to one of them through SerDes — with
or without an external MDIO PHY in front of the cage. This skill
renders the kernel-DT overlay that pairs the BPMP allocation with
kernel-side status="okay" + PHY plumbing on &mgbeN.
Out of scope:
/jetson-customize-uphy. Refuse if
the chosen uphy1-config-N doesn't allocate the target MGBE.mgbeN-speed-*, sub-node mgbeN_status=*) —
owned by /jetson-customize-uphy in its single atomic ODMDATA
commit. This skill MUST NOT touch ODMDATA=.Output is one commit to the composite custom overlay .dts in the
bsp_sources/ hardware repo. /jetson-build-source compiles the
composite to .dtbo and owns its Makefile + flash-conf registration.
ip link show mgbe<N> reports state DOWN
or NO-CARRIER on the configured controller, OR the controller
never appears at all.jetson-customize-uphy ran with uphy1-config-8 (or another config
allocating MGBE) and you now need to bring up the per-controller
side.Prerequisites:
reference_devkit: (Thor) +
custom_carrier: blocks.<source.root_path>/Linux_for_Tegra/.git exists
(/jetson-init-source)./jetson-derive-carrier has run — carrier flash-conf fork is in
the overlay tracker./jetson-customize-uphy chose a UPHY config that allocates the target
MGBE controller's lanes (uphy1-config-8 on Thor for MGBE0..3 25G).custom_carrier: is present, both
documents.custom_carrier_schematic AND
documents.custom_carrier_pinmux_xls are REQUIRED. Refuse the run
if either is missing — MGBE routing on a custom carrier cannot be
guessed. Reference-devkit-only profiles skip this check.dtc on PATH.See references/procedure.md for the full step-by-step procedure (Steps 1–8). Summary:
questions.json (controller, phy_mode, attach kind, I²C bus/addr, reset GPIO, compatible_list).pin_verifier.py for MDC/MDIO/RESET/INT; surface mismatches and route to /jetson-customize-pinmux./jetson-customize-uphy. Step 5 only records the BPMP DTB token-form inspection (sub-node vs top-level) in notes[] for audit..dts; obey the /* custom-bsp: mgbe:mgbe... */ marker contract; run the cpp/dtc/fdtoverlay pre-flight.<profile-stem>.jetson-customize-mgbe.json and emit the one-line + table summary, then drive the downstream chain via sequential AskUserQuestion prompts per references/procedure.md Step 8. Never substitute a printed "Next step: …" line for the prompts./mgbe/mgbe@N subtree — only
mgbe<N>-speed under /uphy. The mgbe<N>_status=disabled
sub-node token is silently rejected on these releases; the whole
ODMDATA line is then dropped at flash time. Always decompile BPMP
DTB (Step 3) before emitting; use the top-level dashed form
(mgbe<N>-speed-del to remove, mgbe<N>-speed-25G to set) when
the sub-node isn't there. Same wrong-form failure surface as
jetson-customize-uphy.mdio child needs both #address-cells = <1> AND
#size-cells = <0> when phy_attach_kind=="phy". Missing either
→ kernel rejects phy@<addr> reg property at probe; MGBE never
comes up.compatible must intersect live DT compatible.
UEFI plugin-manager filters by compatible match. A mismatched
overlay is silently skipped — flash succeeds, MGBE stays disabled,
no error in dmesg. Always sanity-check against
/proc/device-tree/compatible on a booted reference DUT.OVERLAY_DTB_FILE ordering is jetson-build-source's problem,
not this skill's. This skill never touches the carrier flash
conf. The composite custom overlay is registered (by
/jetson-build-source Step 5.0a) AFTER the platform
*-dynamic.dtbo, which is the correct ordering. If you find
yourself appending OVERLAY_DTB_FILE+= in this skill, you're
duplicating ownership — stop, and let the build skill do it.jetson-customize-uphy's job. If the chosen
uphy1-config-N doesn't allocate lanes for the target MGBE
controller, BL31 SError (fmon_update_config: detected fault 0x80) on cold boot. Always run /jetson-customize-uphy first; cite the
chosen uphy1-config-N in this skill's run-summary notes[].jetson-customize-uphy: mgbe<N>_status=disabled for a
controller that's already disabled in BPMP DTB is a no-op the
parser may treat as ambiguous → drops the rest of the ODMDATA
line. Disable via the kernel-DT overlay (status="disabled") only.<bsp_image.root_path>. All
edits land in the overlay tracker / bsp_sources mono-repo under
the pristine + customization commit pattern.jetson-customize-uphy: ODMDATA + overlay .dts + two git
commits are the device-facing outputs; the sidecar is for tooling
and idempotency only.questions.json — Q-1..Q-8 prompt schema
consumed by Step 2.../../scripts/pin_verifier.py
— shared HSIO pin verifier (Step 4).../../references/platform_template.yaml
— documents: block consumed by Step 1.../../context/bsp-customization-workflow.md
— overlay edit protocol (batched pristine + customization commit).../jetson-customize-uphy/SKILL.md — sibling
skill that owns UPHY lane allocation. Must run before this skill to
set uphy1-config-N for MGBE-allocated configurations.../jetson-customize-pinmux/SKILL.md —
sibling skill invoked by Step 4 (with operator confirmation) to
fix pin SFIO mismatches.../jetson-derive-carrier/SKILL.md
— must run first; produces the carrier flash-conf fork edited in
Step 5 and the carrier base overlay this skill orders after.../jetson-init-source/SKILL.md —
produces the overlay tracker + bsp_sources repo this skill commits
into.© 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 7 other files (references, assets) in skills/jetson-customize-mgbe of NVIDIA/skills.
Open the folder on GitHubat commit dfdd080
Jetson Customize Mgbe 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 Mgbe this skillNVIDIA/skills | 3.5k | — | ~2.1k | 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
Enable Jetson Thor 25G/10G/1G MGBE QSFP via kernel-DT overlay. Jetson Customize Mgbe is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Enable Jetson Thor 25G/10G/1G MGBE QSFP via kernel-DT overlay.
Jetson Customize Mgbe fits situations like: UPHY lane allocation; tasks that involve GPU and accelerator computing.
Run `npx skills add NVIDIA/skills --skill jetson-customize-mgbe -a claude-code`. Or copy the skill folder (skills/jetson-customize-mgbe in NVIDIA/skills) into .claude/skills/jetson-customize-mgbe in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill jetson-customize-mgbe -a codex`. Or copy the skill folder (skills/jetson-customize-mgbe in NVIDIA/skills) into .agents/skills/jetson-customize-mgbe 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-mgbe -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-mgbe, .gemini/skills/jetson-customize-mgbe, .github/skills/jetson-customize-mgbe and .opencode/skills/jetson-customize-mgbe in your project.
SKILL.md names no scripts, command-line tools or credentials: Jetson Customize Mgbe is instructions for the agent only.
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. Review the folder before installing.
Jetson Customize Mgbe 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 2.1k tokens (SKILL.md is roughly 8.2k 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 4.9k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Jetson Customize Mgbe: 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.
