复制安装命令
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复制前请先查看来源、License 和安全提示。
Official, NVIDIA-verified Agent Skills for Claude Code, Codex, and other coding agents.
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
Official, NVIDIA-verified Agent Skills for Claude Code, Codex, and other coding agents.
📖 Docs: docs.nvidia.com/skills · 📺 Livestream: From Vulnerable to Verified · 📝 Blog: NVIDIA Verified Agent Skills: Capability Governance for AI Agents
Skills are portable instruction sets that teach AI agents how to use NVIDIA software optimally: Physical AI and robotics workflows, simulation, CUDA-X libraries, RAG and AI Blueprints, and platform tools. This repository is a catalog: skills are maintained in their respective product repos, and mirrored here daily via an automated sync pipeline. Skills are being added continuously, so check back for updates. We are building this infrastructure in the open, and contributions are welcome. See the Roadmap for what is planned next.
Install NVIDIA skills with the default skills CLI flow:
npx skills add nvidia/skills
The CLI runs through npx and prompts you to choose a skill and install destination. You do not need to clone this repo or copy skill folders by hand.
Requires a current
skillsCLI (v1.5.16 or newer). Installing vianpx skills@latest add nvidia/skillsalways uses the latest. On older CLIs (v1.5.15 and earlier), skills may install but not appear in Claude Code — see Troubleshooting.
The skill is available the next time your agent loads skills and encounters a relevant task. For example, ask your agent to "solve a linear programming problem with cuOpt" and the skill guides it through the cuOpt Python API. In Claude Code, run /reload-skills to load newly installed skills in your current session.
Use this when you already know the skill name and want to skip prompts.
npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --yes
Replace cuopt-numerical-optimization-api with any skill name from the Skill Catalog.
Use --agent to target a specific AI coding agent. Initially, we'll support common client targets, expanding the list over time. For the full list of clients supported by the spec, see the skills CLI Supported Agents table.
Claude Code
npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent claude-code
Codex
npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent codex
Snowflake CoCo
npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent cortex
Cursor
npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent cursor
Kiro
npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent kiro-cli
Use --agent more than once to install the same skill into multiple agents.
npx skills add nvidia/skills \
--skill cuopt-numerical-optimization-api \
--agent claude-code \
--agent codex \
--agent cursor \
--agent kiro-cli
New skills land continuously, and existing ones are revised, renamed, or consolidated as the catalog evolves. Refresh what you have installed with:
npx skills update
Run it interactively and the CLI also flags skills that were removed or merged upstream (for example, when several skills are consolidated into one) and offers to remove the stale local copies. Use npx skills list to see what is installed and npx skills check to preview what is out of date first.
Use this when you want to see available NVIDIA skills before installing anything.
npx skills add nvidia/skills --list
For non-interactive installs, global installs, agent-specific installs, updates, removals, and fallback manual copying, see Advanced installation.
Where to file an issue depends on what's broken:
Per-product source repo links:
For issues with this catalog repo itself (README, structure, listing a new product): open an issue here.
Every published skill ships with a detached OMS signature (skill.oms.sig). The sync pipeline drops any skill missing the required artifacts before publishing, so every skill in the catalog carries:
SKILL.md — the skill instructions consumed by the agentskill-card.md — skill identity and governance cardskill.oms.sig — detached OMS signature (verifiable against nv-agent-root-cert.pem)evals/evals.json, evals/*.json, eval/*.json, or benchmark/evals.jsonBENCHMARK.md — generated benchmark report capturing verifiable uplift dataVerify a skill against the NVIDIA trust anchor nv-agent-root-cert.pem:
pip install model-signing
model_signing verify certificate SKILL_DIR \
--signature SKILL_DIR/skill.oms.sig \
--certificate_chain nv-agent-root-cert.pem \
--ignore_unsigned_files
A successful verification confirms that the skill contents have not been modified since signing by NVIDIA.
See Verify Signed Agent Skills for signature layout, the trust pipeline, and policy options.
NVIDIA/skills/
├── skills/ # NVIDIA-verified skills (count grows continuously),
│ │ synced from upstream product repos
│ ├── README.md # Browser-facing install guidance
│ ├── <product-prefix>-*/ # Flat layout — one dir per skill, product-prefixed
│ │ # e.g. aiq-*, cuopt-*, cupynumeric-*,
│ │ # dali-*, deepstream-*, dicom-*, digital-health-*,
│ │ # dynamo-*, earth2studio-*, holoscan-*, hsb-*,
│ │ # jetson-*, launch-nemo-rl, mcore-*,
│ │ # nemo-automodel-*, nemo-data-designer-plugin,
│ │ # nemo-evaluator-plugin, nemo-mbridge-* (20 skills),
│ │ # nemo-retriever, nemo-rl-* (4 skills),
│ │ # nemoclaw-user-guide, nemotron-*, nemotron-speech,
│ │ # nv-* (medical AI), physicsnemo-*, rag-*,
│ │ # skill-card-generator, tao-*, tilegym-*,
│ │ # vss-* (15 skills), accelerated-computing-cudf,
│ │ # cudaq-guide, portfolio-optimization
│ ├── omniverse-*/ # Physical AI — manually staged (see manual-components.yml)
│ └── physical-ai-*/ # Physical AI — manually staged
├── components.d/ # Product registry — one file per component, teams onboard here
│ ├── README.md # Schema and onboarding instructions
│ └── <product>.yml # one file per registered product
├── plugins/ # Packaged plugin distributions
│ └── nvidia-skills/ # Curated NVIDIA skills bundle (Claude Code, Codex)
├── plugins.d/ # Plugin build registry — config for `build-plugins.py`
│ ├── README.md
│ ├── _defaults.yml
│ └── nvidia-skills.yml
├── .claude-plugin/ # Claude Code marketplace metadata
│ └── marketplace.json
├── .agents/plugins/ # Agent marketplace metadata (other clients)
│ └── marketplace.json
├── docs/ # Long-form documentation (published via Fern)
│ ├── README.md # How to build the docs locally
│ ├── index.mdx
│ ├── advanced-install.mdx
│ ├── agent-skill-trust-pipeline.mdx
│ ├── release-checklist.mdx
│ ├── scanning-agent-skills.mdx
│ ├── signing-agent-skills.mdx
│ └── skill-cards.mdx
├── fern/ # Fern docs site configuration
├── .github/
│ ├── workflows/ # Sync pipeline, plugin validation, DCO check, author verify
│ └── scripts/ # regenerate-readme.sh, build-plugins.py,
│ # manual-components.yml (temp Physical AI catalog
│ # exception, removed after Computex 2026),
│ # marketplace/metadata.json (skill metadata sidecar)
├── nv-agent-root-cert.pem # Trust anchor for OMS signature verification
├── skills.sh.json # Skills.sh marketplace grouping config
├── CHANGELOG.md
├── CONTRIBUTING.md # Contribution guidelines
├── SECURITY.md # Security reporting policy
├── CODE_OF_CONDUCT.md # Community code of conduct
├── LICENSE-APACHE # Apache 2.0 (source code)
└── LICENSE-CC-BY-4.0 # CC BY 4.0 (documentation/skills)
Skills are maintained in their respective product repos (see the Source column in the Skill Catalog) and synced to this repo daily. Products only appear under skills/ after the sync pipeline confirms each skill carries:
skill.oms.sig — detached OMS-format signature (verifiable against nv-agent-root-cert.pem)skill-card.md — skill identity and governance cardevals/evals.json, evals/*.json, eval/*.json, or benchmark/evals.jsonWhen evaluation runs produce a BENCHMARK.md, it ships alongside the skill so consumers can see verifiable benchmark uplift data.
This repository adheres to the Agent Skills specification:
SKILL.md file at their root.name and description fields.skills-ref reference library.Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
This code is dual-licensed with documentation/skills under the CC-BY-4.0 AND source code under Apache-2.0 license terms. The full license texts can be found in LICENSE-APACHE and LICENSE-CC-BY-4.0 respectively.
license: Apache-2.0
name: doca-erasure-coding
description: >
Use this skill when the user is doing hands-on DOCA Erasure Coding
programming on a BlueField DPU, ConnectX NIC, or host — bringing
up a doca_ec context, picking among the create / recover / update
tasks, choosing matrix type / N / K / block size, querying
doca_ec_cap_* before sizing, setting doca_mmap src/dst
permissions, or debugging DOCA_ERROR_* returns from
doca_ec_task_*. Trigger even when the user does not name "DOCA
Erasure Coding" or "Reed-Solomon" — typical implicit phrasings
include "one data block changed, how do I refresh parity without
re-encoding", "a disk failed and 2 parity blocks are gone, can I
rebuild", "RAID-6 resilience across 12 disks", "my
doca_ec_task_create returns NOT_PERMITTED", or "is this N+K layout
still recoverable". Refuse and route elsewhere for non-Reed-Solomon
codes (fountain / LDPC / raptor), pure-replication designs,
network FEC, or other DOCA accelerator libraries (SHA / Compress /
AES-GCM / DMA) — those belong to other skills.
metadata:
kind: library
compatibility: >
Requires DOCA SDK installed at /opt/mellanox/doca on Linux (Ubuntu
22.04/24.04 or RHEL/SLES) with a BlueField DPU or ConnectX NIC
attached. Reads the user's local install via `pkg-config
doca-erasure-coding` and inspects
/opt/mellanox/doca/{lib,include,samples,applications}.Where to start: This skill assumes DOCA is already installed and
the user is doing hands-on erasure-coding work on a BlueField /
ConnectX / host with DOCA. Open TASKS.md if the user
wants to do something (configure / build / modify / run / test /
debug); open CAPABILITIES.md when the question
is what can DOCA Erasure Coding express on this version. If the
user has not installed DOCA yet, route to
doca-setup first. If the user is
asking "should I even use erasure coding here, or just replicate
the data?", the path-selection rule in
CAPABILITIES.md ## Capabilities and modes
is the first stop — erasure coding is a storage-resilience
primitive (RAID-6 / distributed file system parity / object-storage
erasure-coded buckets), not a network primitive and not a
replication substitute.
The CLASSES of DOCA Erasure Coding questions this skill is built to answer, each with one worked example. The agent should treat the class as the load-bearing piece — the worked example is a single instance.
CAPABILITIES.md ## Capabilities and modes
CAPABILITIES.md ## Safety policy.doca_ec_task_create on this BlueField, what is the maximum
block size, what is the cap on N+K, and does the device
advertise a Vandermonde Reed-Solomon matrix?". Answered by
the per-task + matrix + size capability-query rule
(doca_ec_cap_task_create_is_supported,
_task_recover_is_supported, _task_update_is_supported,
_task_galois_mul_is_supported — the 4th public task on the
EC accelerator, doca_ec_cap_get_max_block_size,
doca_ec_cap_get_max_buf_list_len, and per-variant
doca_ec_matrix_create() constructor success — the public
header does NOT ship a doca_ec_cap_get_matrix_* family) in
CAPABILITIES.md ## Capabilities and modes
TASKS.md ## configure.doca_ec_task_update row in the
task-type table in
CAPABILITIES.md ## Capabilities and modes
CAPABILITIES.md ## Safety policyTASKS.md ## modify.doca_ec_task_recover row in the task-type table in
CAPABILITIES.md ## Capabilities and modes
TASKS.md ## test.doca_ec_task_create returns
DOCA_ERROR_NOT_PERMITTED". Answered by the permission matrix
in CAPABILITIES.md ## Safety policy
TASKS.md ## test.doca_ec_task_update in
the DOCA I have installed, or do I have to recompute parity from
scratch?". Answered by the version-compatibility overlay in
CAPABILITIES.md ## Version compatibility,
which cross-links the canonical detection chain in
doca-version and adds the
EC-specific "discover per-task support + matrix type via cap
query" bullets.DOCA_ERROR_* from an EC call mean and which
layer caused it?" — worked example: "DOCA_ERROR_INVALID_VALUE
on doca_ec_task_create_allocate_init with block_size = 4 MiB".
Answered by the EC overlay on the cross-library taxonomy in
CAPABILITIES.md ## Error taxonomy
TASKS.md ## debug that escalates to
doca-debug.This skill serves external developers building applications that
consume the DOCA Erasure Coding library — i.e., users whose code
calls doca_ec_* (directly in C/C++, or through FFI/bindings from
another language) to offload Reed-Solomon erasure coding onto a
BlueField DPU or ConnectX accelerator. It is not for NVIDIA
developers contributing to DOCA Erasure Coding itself.
The canonical fit is distributed storage: RAID-6-style block layouts, distributed file system parity, object-storage erasure-coded buckets, and any data-durability workload where the N data + K redundancy block model lets the system tolerate K simultaneous block losses without data loss. The skill keeps the agent oriented to that domain: erasure coding is operationally distinct from pure replication (which keeps M whole copies) and from RAID-6 the disk layout (which is one specific instance of the N=k, K=2 case); confusing them produces wrong recommendations.
Language scope. DOCA Erasure Coding ships as a C library with
pkg-config module name doca-erasure-coding. The shipped samples
are written in C. C and C++ consumers are the canonical case and
the worked examples in TASKS.md assume that path. Other-language
consumers (Rust, Go, Python, …) consume the same *.so through
FFI or language-specific bindings; the skill's contribution in
that case is to keep the lifecycle, capability-discovery,
permission, error-taxonomy, and create-vs-recover-vs-update
guidance language-neutral, and to route the agent to the public C
ABI as the authoritative surface that any wrapper will eventually
call.
Load this skill when the user is doing hands-on DOCA Erasure Coding work, in any language. Concretely:
doca_ec context on a doca_dev and configuring
at least one task type (doca_ec_task_create,
doca_ec_task_recover, and/or doca_ec_task_update) before
doca_ctx_start().doca_mmap correctly for the source
buffers — data blocks for create, data + parity for recover —
(DOCA_ACCESS_FLAG_LOCAL_READ_ONLY at minimum) and the
destination buffers — redundancy blocks for create, recovered
blocks for recover, updated parity for update —
(DOCA_ACCESS_FLAG_LOCAL_READ_WRITE).doca_ec_cap_get_max_block_size(devinfo) and N+K against
doca_ec_cap_get_max_buf_list_len(devinfo, &max_buf_list_len).doca_ec_cap_task_*_is_supported (including the 4th task
_task_galois_mul_is_supported) and per-variant
doca_ec_matrix_create() constructor success — the public
header does NOT ship a doca_ec_cap_get_matrix_*
families against the active doca_devinfo.doca_ec_task_update
is far cheaper than recomputing all K parity blocks via a fresh
doca_ec_task_create).DOCA_ERROR_* returned from an EC call (lifecycle
vs. block-size vs. N+K vs. matrix-type vs. permission vs.
queue pressure) and the task-completion event on the progress
engine.Do not load this skill for general DOCA orientation, install
of DOCA itself, non-Reed-Solomon erasure codes (fountain codes,
LDPC — those belong on a CPU library, not the DOCA accelerator),
pure replication / mirroring designs (erasure coding is the wrong
primitive when one extra copy is the right answer), or other
DOCA libraries. For those, use
doca-public-knowledge-map.
This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive EC-specific material lives in two companion files:
CAPABILITIES.md — what DOCA Erasure Coding can express on
this version: the three task types (create / recover / update,
each independently capability-gated), the matrix-type + N + K +
block-size configuration surface, the capability-query family
(doca_ec_cap_* for task support, max block size, max N+K,
supported matrix types), the EC error taxonomy (mapped onto
the cross-library DOCA_ERROR_* set), the observability
surface (per-task completion events on the progress engine),
the safety policy that gates source / destination mmap
permission decisions, and the path-selection rule (when to use
doca-erasure-coding versus a CPU EC library versus pure
replication versus RAID-6 on disk).TASKS.md — step-by-step workflows for the six in-scope EC
verbs: configure, build, modify, run, test, debug.
Plus a Deferred task verbs block that points out-of-scope
questions at the right next skill.The skill assumes a host or BlueField where DOCA is already
installed at the standard location and the user has the
privileges their public install profile expects. It does not
cover installing DOCA — that path goes through
doca-setup.
This skill is agent guidance, not a samples or templates bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
/opt/mellanox/doca/samples/doca_erasure_coding/.
The agent's job is to route the user to those files and
prescribe a minimum-diff modification on them via the universal
modify-a-sample workflow in
doca-programming-guide,
layered with the EC-specific overrides in
TASKS.md ## modify.meson.build,
CMakeLists.txt, Cargo.toml, …) parked inside the skill.
The agent constructs the build manifest in the user's
project directory against the user's installed DOCA, where
pkg-config --modversion doca-erasure-coding is the source of
truth.samples/, bindings/, or reference/ subtree of any
kind. A mock or incomplete artifact in this skill's tree, even
one labeled "reference", is misleading: users will read it as
buildable.SKILL.md first to confirm the user's question is in
scope (storage-domain resilience — N data + K redundancy
blocks — and not a network or replication question
misclassified as erasure coding).Both companion files cross-link to each other,
doca-version for the canonical
version-handling rules, and
doca-public-knowledge-map
whenever the right answer is "look it up in the public docs or
the installed package layout" rather than "EC-specific guidance".
doca-public-knowledge-map —
the routing table for every public DOCA documentation source
and the on-disk layout of an installed DOCA package. The DOCA
Erasure Coding page lives at
https://docs.nvidia.com/doca/sdk/DOCA-Erasure-Coding/index.html;
the install-tree layout (samples directory, header location)
belongs to the public knowledge map, not to this skill.doca-setup — env preparation,
install verification, and the I have no install yet path
with the public NGC DOCA container. This skill assumes its
preconditions are satisfied.doca-version — canonical DOCA
version-handling rules. This skill's
## Version compatibility
cross-links the four-way match rule and adds only the
EC-specific "discover per-task support + supported matrix
types + max block size + max N+K via cap query" overlay.doca-structured-tools-contract —
the bundle's structured-tools precedence rule (detect / prefer
/ fall back / report). The Command appendix in
TASKS.md honors this contract.doca-programming-guide —
general DOCA programming patterns shared by every library: the
canonical pkg-config + meson build pattern, the universal
modify-a-shipped-sample first-app workflow, the universal
lifecycle, the cross-library DOCA_ERROR_* taxonomy, and the
program-side debug order. This skill layers EC specifics on
top.doca-debug — the cross-cutting
debug ladder (install / version / build / link / runtime /
program / driver). EC-specific debug (task-not-supported,
matrix-type-unsupported, block-size-over-max, N+K-over-max,
recover-with-too-many-missing) overlays on top of that ladder.
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