Graphsignal
graphsignal/graphsignal
Profile AI inference workloads (vLLM, SGLang, TensorRT-LLM, PyTorch, any GPU application) with the Graphsignal profiler and read the results from its local /signals JSON endpoint.
A skill your agent uses for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill.
Install Nvidia Skill Finder
$ npx skills add NVIDIA/skills --skill nvidia-skill-finder -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills nvidia-skill-finder --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/nvidia-skill-finder .claude/skills/nvidia-skill-finder && 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 "nvidia-skill-finder" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-skill-finder into .claude/skills/nvidia-skill-finder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-skill-finder", 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/nvidia-skill-finderType 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 nvidia-skill-finder -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills nvidia-skill-finder --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/nvidia-skill-finder .agents/skills/nvidia-skill-finder && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nvidia-skill-finder" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-skill-finder into .agents/skills/nvidia-skill-finder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-skill-finder", 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 nvidia-skill-finder -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills nvidia-skill-finder --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/nvidia-skill-finder .cursor/skills/nvidia-skill-finder && 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 "nvidia-skill-finder" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-skill-finder into .cursor/skills/nvidia-skill-finder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-skill-finder", 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/nvidia-skill-finder--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 nvidia-skill-finder -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills nvidia-skill-finder --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/nvidia-skill-finder .gemini/skills/nvidia-skill-finder && 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 "nvidia-skill-finder" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-skill-finder into .gemini/skills/nvidia-skill-finder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-skill-finder", 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 nvidia-skill-finderInstalls 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 nvidia-skill-finder -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/nvidia-skill-finder .github/skills/nvidia-skill-finder && 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 "nvidia-skill-finder" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-skill-finder into .github/skills/nvidia-skill-finder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-skill-finder", 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 nvidia-skill-finder -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 nvidia-skill-finder --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/nvidia-skill-finder .opencode/skills/nvidia-skill-finder && 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 "nvidia-skill-finder" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/nvidia-skill-finder into .opencode/skills/nvidia-skill-finder/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nvidia-skill-finder", 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
nvidia-skill-finder- GitHub stars
- 3.5k
- Token cost
- ~2.1k tokens
- SKILL.md length
- 1,047 words
- Files
- 7 (incl. references)
- Skills in repo
- 380
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
A skill your agent uses for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill.
- Works in 2 steps: Check whether the relevant NVIDIA skill… → Query the live catalog before naming a…
- NVIDIA-related requests where an NVIDIA skill might help
- SKILL.md covers Purpose, When to Use this Skill, Implicit Invocation Constraints and When Not to Use this Skill, plus 4 more sections
- Calls npx; reaches build.nvidia.com
What it does
Nvidia Skill Finder is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software, SDKs, GPUs, Jetson/JetPack/L4T/BSP/SDK Manager/driver/flashing/setup, CUDA, NIM, NeMo, Omniverse/OpenUSD/SimReady, Isaac, RAPIDS/cuDF, cuPyNumeric, cuOpt, Dynamo, Holoscan, TensorRT, DeepStream, VSS, TAO, NGC/NVCF. Do not use for generic non-NVIDIA route, optimize, deploy, AI, video, data, or infrastructure tasks.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `BENCHMARK.md`, `agents/openai.yaml` and `evals/evals.json`).
It sits in AI & LLM Engineering, covering GPU and accelerator computing, LLM inference and serving and AI video generation. It works with NVIDIA AI Platform and CUDA. 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
- NVIDIA-related requests where an NVIDIA skill might help
- Even if the user did not ask for a skill
- NVIDIA products
- Jetson/JetPack/L4T/BSP/SDK Manager/driver/flashing/setup
Example prompts
- “/nvidia-skill-finder”
Requirements
- Node.js
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Check whether the relevant NVIDIA skill is already installed or already in context. If it is, hand off to that skill instead of…
- Query the live catalog before naming a specific install target or giving the
What it can do on your machine
Read from SKILL.md and the folder at commit 0e0d506. 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:
npx
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
build.nvidia.com
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
Nvidia Skill Finder loads about 2.1k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 123 tokens; SKILL.md has 1,047 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.
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 0e0d506, republished under its Apache-2.0 licence (© NVIDIA). 1,047 words, ~2,086 tokens.
Download SKILL.mdSave it as
.claude/skills/nvidia-skill-finder/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- nvidia-skill-finder
- description
- Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software, SDKs, GPUs, Jetson/JetPack/L4T/BSP/SDK Manager/driver/flashing/setup, CUDA, NIM, NeMo, Omniverse/OpenUSD/SimReady, Isaac, RAPIDS/cuDF, cuPyNumeric, cuOpt, Dynamo, Holoscan, TensorRT, DeepStream, VSS, TAO, NGC/NVCF. Do not use for generic non-NVIDIA route, optimize, deploy, AI, video, data, or infrastructure tasks.
- license
- CC-BY-4.0 AND Apache-2.0
- metadata.author
- NVIDIA
- metadata.tags
- nvidia, skills, discovery, catalog, router
- metadata.domain
- agent-skills
NVIDIA Skill Finder
Purpose
Help users discover, install, and start using NVIDIA skills that may not be installed yet. Treat this skill as a stable NVIDIA capability detector and catalog router, not as a mirror of every external skill's trigger text.
Use the live catalog as the source of truth for specific skill names, descriptions, and availability. Keep only stable taxonomy guidance here.
When to Use this Skill
Use this skill to find the best NVIDIA skill for a product, task, or workflow. The user does not need to explicitly ask for a skill. If the request is about NVIDIA hardware, software, SDKs, drivers, setup, troubleshooting, or an NVIDIA-adjacent workflow, check whether the live catalog has a skill that could help before proceeding too far with general guidance.
Typical triggers:
- Asks "how do I do X" where X might be a common task that an NVIDIA skill can help with.
- Says "find a skill for X" or "is there a skill for X".
- Expresses interest in extending agent capabilities in NVIDIA domains.
- Mentions they need help with a specific NVIDIA catalog domain covered below.
- Asks about installing, configuring, troubleshooting, or using an NVIDIA product, device, SDK, or service.
Continue with this skill only when the request is plausibly related to an NVIDIA product area or taxonomy category.
Strong signals:
- The user mentions NVIDIA, CUDA, GPU acceleration, NIM, NeMo, Omniverse, OpenUSD, SimReady, Isaac, cuOpt, RAPIDS/cuDF, cuPyNumeric, Dynamo, Holoscan, TensorRT, VSS, DeepStream, Jetson, JetPack, L4T, BSP, SDK Manager, TAO, NGC, NVCF, or another NVIDIA product.
- The task maps strongly to an NVIDIA catalog lane such as Agentic AI, Physical AI, Robotics, Vision AI, Conversational AI, Simulation and Modeling, Data Science, Training AI, Inference AI, Decision Optimization, GPU Development, Quantum Computing, Infrastructure, or Networking.
- The task uses distinctive phrases such as RAG/deep research, vehicle routing, LP/MILP/QP, GPU DataFrames, multi-GPU NumPy/SciPy, KV-aware routing, Jetson driver install, JetPack flashing, BSP download, SDK Manager setup, CAD-to-SimReady, OpenUSD optimization, VSS/video search/summarization, DICOM workflows, robotics simulation, Holoscan setup, or synthetic data generation.
Read references/taxonomy-routing.md only when the request is taxonomy-only, ambiguous, or needs browse/domain mapping. For obvious product-name matches, go directly to live catalog lookup.
Implicit Invocation Constraints
Implicit invocation is intentional: this skill acts as a NVIDIA capability detector and catalog router. This scopes the skill to NVIDIA relevance; it does not narrow it. Use the full trigger breadth in "When to Use this Skill" — including the softer "how do I do X" triggers and any request plausibly related to an NVIDIA product area or catalog taxonomy lane.
The gate is relevance, not consent. Do not activate for the generic software tasks in "When Not to Use this Skill" unless they also carry an NVIDIA, GPU, accelerated-computing, or distinctive NVIDIA workflow signal.
Recommending a skill is always allowed once the request is relevant. Installing
or modifying skills is not: never run an install (e.g. npx skills add) or
change agent capabilities without explicit user approval. A catalog match is
only a recommendation until the user confirms.
When Not to Use this Skill
Stay quiet when the request is generic:
- "route" means an HTTP route, Express route, file route, or request routing.
- "optimize" means ordinary web performance, CSS, bundle size, SQL tuning, or generic code cleanup.
- "deploy" means generic Kubernetes, cloud, CI/CD, or web hosting.
- "AI", "data science", or "infrastructure" appears without NVIDIA, GPU, accelerated-computing, or one of the distinctive intent signals above.
- "video" means ordinary trimming, captions, export, or social-media editing.
If relevance is uncertain, do not interrupt the user's main task. Mention the NVIDIA catalog only as an optional aside after answering, or ask one concise clarifying question if the choice materially changes the work.
Show full SKILL.md (438 more words)Show less
Instructions
How to Help Users Find Skills - a Discovery Workflow
This skill's first job is skill discovery. For NVIDIA-related requests, do a catalog check before using general web search, NVIDIA product docs, or general product knowledge as the main answer. Product documentation can help after the catalog check, but it is not a substitute for checking the NVIDIA skills catalog.
Catalog check means one of:
npx skills add nvidia/skills --listhttps://github.com/NVIDIA/skills/tree/main/skillshttps://build.nvidia.com/skillshttps://raw.githubusercontent.com/NVIDIA/skills/main/skills.sh.json
- Check whether the relevant NVIDIA skill is already installed or already in context. If it is, hand off to that skill instead of recommending install.
- Query the live catalog before naming a specific install target or giving the main product answer. When shell access is available, attempt this command first:
npx skills add nvidia/skills --listUse the fallback catalog sources only if the CLI is unavailable, blocked, or fails:
- https://github.com/NVIDIA/skills/tree/main/skills
- https://build.nvidia.com/skills
- https://raw.githubusercontent.com/NVIDIA/skills/main/skills.sh.json
Do not count a general web search, developer.nvidia.com product documentation, or docs.nvidia.com product documentation as the catalog check.
- Match the request against current skill names, descriptions, product groups, and skill cards. Prefer NVIDIA-verified catalog entries over memory.
- If a current catalog skill strongly matches, recommend it before continuing with general product guidance. Recommend at most three skills, ordered by confidence. For each, include: skill name, why it fits, install command, and first useful prompt.
- Ask before installing. Do not run
npx skills addunless the user approves.
Recommendation Format
For a strong match that is not installed:
The NVIDIA <product or skill family> skill could help with this. Would you like me to install <skill-name>?Use the active agent target when known:
npx skills add nvidia/skills --skill <skill-name> --agent codex --global --yes
npx skills add nvidia/skills --skill <skill-name> --agent claude-code --global --yesIf the agent target is unknown, omit --agent and let the CLI prompt:
npx skills add nvidia/skills --skill <skill-name> --global --yesAfter install, tell the user to restart or reload the agent if their client does not pick up newly installed skills immediately.
Confidence Rules
- High confidence: product name or distinctive intent maps cleanly to one current catalog skill or skill family.
- Medium confidence: taxonomy lane matches but several skills may apply. Offer a short shortlist and ask which direction matches the user's task.
- Low confidence: only generic wording matches. Do the user's task without recommending an NVIDIA skill.
Do not fabricate catalog entries or guess at skill names. If catalog lookup
fails, say the catalog could not be checked and do not name a concrete slug or
emit an npx skills add ... --skill <name> install command. Offer to share the
catalog URL, retry lookup, or continue with general help.
When No Skills are Found
Say that no strong NVIDIA catalog match was found, then either:
- search the broader ecosystem with npx skills find
<query>, or - offer to help directly without a skill, or
- suggest creating a new skill if the workflow is recurring.
© 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 6 other files (references) in skills/nvidia-skill-finder of NVIDIA/skills.
- SKILL.md
- BENCHMARK.md
- agents/openai.yaml
- evals/evals.json
- references/taxonomy-routing.md
- skill-card.md
- skill.oms.sig
Open the folder on GitHubat commit 0e0d506
Compare with similar skills
Nvidia Skill Finder 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 |
|---|---|---|---|---|---|---|
| Nvidia Skill Finder this skillNVIDIA/skills | 3.5k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Graphsignalgraphsignal/graphsignal | 257 | — | ~6.2k | Automated safety check: Pass | Apache-2.0 | |
| LLM Torch Profiler Trace AnalysisBBuf/AI-Infra-Auto-Driven-SKILLS | 900 | — | ~2.8k | Automated safety check: Pass | None | |
| TensorRT-LLM InferenceOrchestra-Research/AI-Research-SKILLs | 13k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Llama CppOrchestra-Research/AI-Research-SKILLs | 13k | 4 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Cv DeployLMIXR/CV_Deployment_skill | 126 | — | ~547 | Automated safety check: Pass | None |
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Related
Works with
Categories
Questions about Nvidia Skill Finder
What does Nvidia Skill Finder do?
A skill your agent uses for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Nvidia Skill Finder is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill.
When should I use Nvidia Skill Finder?
Nvidia Skill Finder fits situations like: NVIDIA-related requests where an NVIDIA skill might help; even if the user did not ask for a skill; NVIDIA products; jetson/JetPack/L4T/BSP/SDK Manager/driver/flashing/setup.
How do I install Nvidia Skill Finder in Claude Code?
Run `npx skills add NVIDIA/skills --skill nvidia-skill-finder -a claude-code`. Or copy the skill folder (skills/nvidia-skill-finder in NVIDIA/skills) into .claude/skills/nvidia-skill-finder in your project. Claude Code loads it when a task matches its description.
How do I install Nvidia Skill Finder in Codex?
Run `npx skills add NVIDIA/skills --skill nvidia-skill-finder -a codex`. Or copy the skill folder (skills/nvidia-skill-finder in NVIDIA/skills) into .agents/skills/nvidia-skill-finder in your project. Codex loads it when a task matches its description.
Can I use Nvidia Skill Finder 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 nvidia-skill-finder -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nvidia-skill-finder, .gemini/skills/nvidia-skill-finder, .github/skills/nvidia-skill-finder and .opencode/skills/nvidia-skill-finder in your project.
What does Nvidia Skill Finder need to run?
Going by SKILL.md and its folder, Nvidia Skill Finder needs the command-line tools its instructions call (npx). Our summary lists: Node.js.
Does Nvidia Skill Finder access the network?
SKILL.md names 1 domain. In commands or code: build.nvidia.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Nvidia Skill Finder 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 Nvidia Skill Finder use?
Nvidia Skill Finder 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 Nvidia Skill Finder use?
About 2.1k tokens (SKILL.md is roughly 8.3k 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 887 tokens, read only when the agent opens those files.
What are the alternatives to Nvidia Skill Finder?
Skills that share tags, products or a category with Nvidia Skill Finder: Graphsignal (graphsignal/graphsignal, 257 stars), LLM Torch Profiler Trace Analysis (BBuf/AI-Infra-Auto-Driven-SKILLS, 900 stars), TensorRT-LLM Inference (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Llama Cpp (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Nvidia Skill Finder?
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,534 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.