nvidia-skill-finder

# 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, 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](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.

## 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 --list`
- `https://github.com/NVIDIA/skills/tree/main/skills`
- `https://build.nvidia.com/skills`
- `https://raw.githubusercontent.com/NVIDIA/skills/main/skills.sh.json`

1. 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.
2. 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:

```bash
npx skills add nvidia/skills --list
```

Use 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.

3. Match the request against current skill names, descriptions, product groups, and skill cards. Prefer NVIDIA-verified catalog entries over memory.
4. 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.
5. Ask before installing. Do not run `npx skills