Official agent skill

Jetson Headless Mode

Plan and apply safe Jetson headless-mode changes to reclaim GUI and daemon memory.

OfficialApache-2.0Auto-check passedAI & LLM Engineering

Install Jetson Headless Mode

skills CLI

$ npx skills add NVIDIA/skills --skill jetson-headless-mode -a claude-code

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

GitHub CLI

$ gh skill install NVIDIA/skills jetson-headless-mode --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-headless-mode .claude/skills/jetson-headless-mode && 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/

Paste into Claude Code

Install the "jetson-headless-mode" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-headless-mode into .claude/skills/jetson-headless-mode/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-headless-mode", 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

$skill-installer install https://github.com/NVIDIA/skills/tree/main/skills/jetson-headless-mode

Type 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.

skills CLI

$ npx skills add NVIDIA/skills --skill jetson-headless-mode -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills jetson-headless-mode --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/jetson-headless-mode .agents/skills/jetson-headless-mode && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "jetson-headless-mode" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-headless-mode into .agents/skills/jetson-headless-mode/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-headless-mode", 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.

skills CLI

$ npx skills add NVIDIA/skills --skill jetson-headless-mode -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills jetson-headless-mode --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/jetson-headless-mode .cursor/skills/jetson-headless-mode && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "jetson-headless-mode" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-headless-mode into .cursor/skills/jetson-headless-mode/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-headless-mode", 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

$ gemini skills install https://github.com/NVIDIA/skills.git --path skills/jetson-headless-mode

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add NVIDIA/skills --skill jetson-headless-mode -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills jetson-headless-mode --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/jetson-headless-mode .gemini/skills/jetson-headless-mode && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "jetson-headless-mode" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-headless-mode into .gemini/skills/jetson-headless-mode/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-headless-mode", 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.

GitHub CLI

$ gh skill install NVIDIA/skills jetson-headless-mode

Installs 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).

skills CLI

$ npx skills add NVIDIA/skills --skill jetson-headless-mode -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/jetson-headless-mode .github/skills/jetson-headless-mode && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "jetson-headless-mode" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-headless-mode into .github/skills/jetson-headless-mode/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-headless-mode", 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.

skills CLI

$ npx skills add NVIDIA/skills --skill jetson-headless-mode -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install NVIDIA/skills jetson-headless-mode --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/jetson-headless-mode .opencode/skills/jetson-headless-mode && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "jetson-headless-mode" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/jetson-headless-mode into .opencode/skills/jetson-headless-mode/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jetson-headless-mode", 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.

Facts

Skill name: jetson-headless-mode
GitHub stars: 3.5k
Used in: 1 other repo
Token cost: ~1.9k tokens
SKILL.md length: 898 words
Files: 7 (incl. scripts)
Skills in repo: 380
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Plan and apply safe Jetson headless-mode changes to reclaim GUI and daemon memory.

Works in 4 steps: Run scripts/plan.sh to read audit.json… → Show the plan to the user and confirm. → Run scripts/apply.sh --plan plan.json… → …
Tasks that involve GPU and accelerator computing
SKILL.md covers Purpose, When to use, When NOT to use and Prerequisites, plus 8 more sections
Runs Shell scripts from its folder; calls bash

What it does

Jetson Headless Mode is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Plan and apply safe Jetson headless-mode changes to reclaim GUI and daemon memory.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts (for example `BENCHMARK.md`, `evals/evals.json` and `scripts/apply.sh`).

It sits in AI & LLM Engineering, covering GPU and accelerator computing. It works with NVIDIA AI Platform and Linux. 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

Example prompts

“/jetson-headless-mode”

Requirements

A Bash shell
Docker

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

Run scripts/plan.sh to read audit.json (from jetson-memory-audit) and emit a plan with only safety: safe knobs (target switch, display…
Show the plan to the user and confirm.
Run scripts/apply.sh --plan plan.json for a dry run. Re-run with --apply to execute. Add --drop-caches to flush the page cache afterward…
Re-run jetson-memory-audit/scripts/audit.sh to verify the actual delta.

What it can do on your machine

Read from SKILL.md and the folder at commit 67a13c0. 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
Ships 2 files in scripts/ (Shell), which the agent can run.
Shell commands in SKILL.md call:
- bash
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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 Headless Mode loads about 1.9k tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 898 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~26
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from NVIDIA/skills at commit 67a13c0, republished under its Apache-2.0 licence (© NVIDIA). 898 words, ~1,927 tokens.

Download SKILL.mdSave it as .claude/skills/jetson-headless-mode/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.

name: jetson-headless-mode
description: Plan and apply safe Jetson headless-mode changes to reclaim GUI and daemon memory.
version: 0.0.1
license: Apache-2.0
metadata.author: Jetson Team
metadata.tags: jetson, headless, memory
metadata.languages: bash
metadata.data-classification: public

Jetson Headless Mode

Plan-then-apply for safe, reversible user-space memory reclamation: switch the default systemd target away from graphical.target and disable a curated set of non-essential daemons. This is the highest-yield, lowest-risk memory win on Jetson.

Purpose

Build a user-approved headless-mode plan from live audit data, then apply only safe, reversible user-space changes that reduce desktop and daemon memory use on Jetson.

When to use

"Free as much memory as possible — I don't need the GUI."
"I'm shipping this Jetson as an inference appliance / edge node."
After jetson-memory-audit shows default_systemd_target=graphical.target or shows gdm3 / lightdm / sddm active on a system the user describes as headless.

When NOT to use

The user needs the local desktop, display output, kiosk UI, or any X/Wayland session. In that case, do not recommend disabling the graphical target or display manager; use jetson-memory-audit for a read-only view and suggest non-GUI memory options instead.
You do not have current audit data. Run jetson-memory-audit first, or ask the user for its output, before proposing changes or estimating savings.

Use live device data as the source of truth. Jetson family, SKU/variant, memory totals, active display services, and savings estimates must come from jetson-diagnostic/scripts/detect_jetson.sh, audit.json, or a fresh jetson-memory-audit run. If a value is not available, say it is unknown instead of guessing. The savings numbers below are upper bounds; the real delta is whatever a before/after audit reports.

Prerequisites

Start from a current jetson-memory-audit JSON snapshot.
Confirm the user does not need the local desktop, display output, kiosk UI, or X/Wayland session.
Mutating changes require sudo and explicit user approval; dry-run first unless approval was already given in the same prompt.
Run on the Jetson host or in a host-visible sandbox with access to systemd state.

Available Scripts

Script	Purpose	Arguments
`scripts/plan.sh`	Reads a memory audit JSON and emits a plan containing safe, reversible recommendations.	`--audit PATH` or `--audit -`, plus `--human`.
`scripts/apply.sh`	Prints or applies the safe commands from a plan JSON. Dry-run by default.	`--plan PATH` or `--plan -`, `--apply`, `--reboot`, `--drop-caches`.

If your agent runtime supports run_script, use it to run scripts/plan.sh and scripts/apply.sh and summarize the returned output. Otherwise run the scripts with bash from the repository root.

Instructions

Run scripts/plan.sh to read audit.json (from jetson-memory-audit) and emit a plan with only safety: safe knobs (target switch, display managers, audio, print, modem, etc.).
Show the plan to the user and confirm.
Run scripts/apply.sh --plan plan.json for a dry run. Re-run with --apply to execute. Add --drop-caches to flush the page cache afterward, or --reboot to take effect immediately.
Re-run jetson-memory-audit/scripts/audit.sh to verify the actual delta.

Expected workflow

Use the scripts for estimates and application so recommendations are based on the current device state rather than the static upper-bound table alone.

For "what would headless save", "estimate", "plan", or production planning prompts, run scripts/plan.sh --audit <audit.json> and report estimated_total_savings_mb, the top recommendations[*].knob, and whether any display manager or graphical.target is active. Do not run apply.sh.
For prompts where the user explicitly says to apply headless mode now, run scripts/apply.sh --plan <plan.json> once as a dry run first. If the user has already approved mutation in the same prompt, re-run the same command with --apply and mention the reversible command(s).
If direct execution fails in an agent runtime, invoke scripts with bash {baseDir}/scripts/<script-name> .... Do not try to chmod installed skill files.

Show full SKILL.md (343 more words)Show less

Plan / apply contract

plan.sh emits the same JSON shape as jetson-inference-mem-tune/scripts/recommend.py: an array of recommendations with {layer, knob, estimated_savings_mb, safety, command, reversible_command, rationale}.
apply.sh filters entries to safety == "safe" with a non-empty command, then re-checks the filtered safety marker in the shell loop before execution. Anything else, such as kernel command-line changes, device-tree changes, or accuracy tradeoffs, is out of scope for this skill.
Default mode is dry-run. --apply is required to mutate the system.

Knobs covered

Knob	Action	Estimated savings	Reversible?
`disable-graphical-target`	`systemctl set-default multi-user.target`	up to 865 MB	yes
`stop-gdm3` / `gdm` / `lightdm` / `sddm` / `display-manager`	`systemctl disable --now <svc>`	~200 MB / svc	yes
`stop-pulseaudio`	disable audio daemon	~8 MB	yes
`stop-bluetooth`	disable Bluetooth stack	~6 MB	yes
`stop-ModemManager`	disable WWAN manager	~4 MB	yes
`stop-cups` / `stop-cups-browsed`	disable print stack	~5 / ~3 MB	yes
`stop-snapd`	disable Snap daemon	~30 MB	yes
`stop-whoopsie` / `kerneloops`	disable crash reporters	~4 / ~2 MB	yes
`stop-avahi-daemon`	disable mDNS	~3 MB	yes
`stop-unattended-upgrades` / `packagekit`	disable background package work	~6 / ~8 MB	yes

Do NOT disable these services

nvargus-daemon — required for any libargus camera pipeline.
nvgetty.service — serial console; disabling can lock you out of recovery.
nvpmodel — power-mode service; required for clock/power tuning.
containerd / docker — leave on if you run containers (most inference workloads do).
nvfb / nvdisplay-related kernel services — tied to boot-time display configuration, so this skill does not change them.

Safety

Does not edit /boot/extlinux/extlinux.conf, the device tree, or boot-time memory reservations.
Does not disable services it does not have an explicit entry for (no blanket "disable everything not whitelisted").
Every applied change has a documented reversible_command. Re-running the plan with the reverts is sufficient to restore.
Dry-run by default. --apply is the only way to mutate.
Report only device facts and savings figures that came from live detection or audit output.

Cross-platform behavior

The same set of knobs applies to every Jetson family in the matrix above. The script reads JETSON_GENERATION / JETSON_PRODUCT_LINE / JETSON_VARIANT from jetson-diagnostic/scripts/detect_jetson.sh (and still exports legacy JETSON_SKU) so the agent can attribute the savings correctly in its summary, but it does not branch on product line.

Files

SKILL.md and 6 other files (scripts) in skills/jetson-headless-mode of NVIDIA/skills.

SKILL.md
BENCHMARK.md
evals/evals.json
scripts/apply.sh
scripts/plan.sh
skill-card.md
skill.oms.sig

Open the folder on GitHubat commit 67a13c0

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in NVIDIA/skills, which our catalogue first saw on October 7, 2026.

NVIDIA-AI-IOT/jetson-device-skillsskills/jetson-headless-mode

Compare with similar skills

Jetson Headless Mode 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 Headless Mode compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Jetson Headless Mode this skillNVIDIA/skills	3.5k	1 repos	~1.9k	Automated safety check: Pass	Apache-2.0	today
Graphsignalgraphsignal/graphsignal	257	—	~6.2k	Automated safety check: Pass	Apache-2.0	10 days ago
LLM Torch Profiler Trace AnalysisBBuf/AI-Infra-Auto-Driven-SKILLS	911	—	~2.8k	Automated safety check: Pass	None	3 days ago
TensorRT-LLM InferenceOrchestra-Research/AI-Research-SKILLs	13k	5 repos	~1.3k	Automated safety check: Pass	MIT	3 mo ago
Cv DeployLMIXR/CV_Deployment_skill	146	—	~547	Automated safety check: Pass	None	9 days ago
Megatron-Core LLM TrainingOrchestra-Research/AI-Research-SKILLs	13k	3 repos	~2.4k	Automated safety check: Pass	MIT	3 mo ago

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Works with

Questions about Jetson Headless Mode

What does Jetson Headless Mode do?

Plan and apply safe Jetson headless-mode changes to reclaim GUI and daemon memory. Jetson Headless Mode is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Plan and apply safe Jetson headless-mode changes to reclaim GUI and daemon memory.

When should I use Jetson Headless Mode?

Jetson Headless Mode fits situations like: tasks that involve GPU and accelerator computing.

How do I install Jetson Headless Mode in Claude Code?

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

How do I install Jetson Headless Mode in Codex?

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

Can I use Jetson Headless Mode 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-headless-mode -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-headless-mode, .gemini/skills/jetson-headless-mode, .github/skills/jetson-headless-mode and .opencode/skills/jetson-headless-mode in your project.

What does Jetson Headless Mode need to run?

Going by SKILL.md and its folder, Jetson Headless Mode needs a shell for the scripts in its folder and the command-line tools its instructions call (bash). Our summary lists: A Bash shell; Docker.

Does Jetson Headless Mode access the network?

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.

Is Jetson Headless Mode 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Jetson Headless Mode use?

Jetson Headless Mode 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 Headless Mode use?

About 1.9k tokens (SKILL.md is roughly 7.7k 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 Headless Mode?

Skills that share tags, products or a category with Jetson Headless Mode: Graphsignal (graphsignal/graphsignal, 257 stars), LLM Torch Profiler Trace Analysis (BBuf/AI-Infra-Auto-Driven-SKILLS, 911 stars), TensorRT-LLM Inference (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Cv Deploy (LMIXR/CV_Deployment_skill, 146 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jetson Headless Mode?

NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,539 GitHub stars. The repository holds 380 skills in this directory. The repository was last updated on October 7, 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.

Install Jetson Headless Mode

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Runs code

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SKILL.md

Jetson Headless Mode

Purpose

When to use

When NOT to use

Prerequisites

Available Scripts

Instructions

Expected workflow

Plan / apply contract

Knobs covered

Do NOT disable these services

Safety

Cross-platform behavior

Files

Used in 1 other repository

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