Cv Deploy
LMIXR/CV_Deployment_skill
基于 helpfile 工程经验，协助 agent 配置 CV 主机和边缘设备环境、编译视觉与推理依赖、接入摄像头视频并打包部署服务。适用于 Ubuntu、CentOS、Windows、macOS、Jetson、树莓派和 RK3399 的 CV 工程实施与故障排查，以及相关移动端配套工具；模型训练和纯算法设计不属于本技能主线。
Validate that a Dynamo deployment's NIXL/UCX/NCCL interconnect is ready for disaggregated serving over RDMA/NVLink.
Install Dynamo Interconnect Check
$ npx skills add NVIDIA/skills --skill dynamo-interconnect-check -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills dynamo-interconnect-check --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/dynamo-interconnect-check .claude/skills/dynamo-interconnect-check && 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 "dynamo-interconnect-check" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-interconnect-check into .claude/skills/dynamo-interconnect-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-interconnect-check", 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/dynamo-interconnect-checkType 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 dynamo-interconnect-check -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills dynamo-interconnect-check --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/dynamo-interconnect-check .agents/skills/dynamo-interconnect-check && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dynamo-interconnect-check" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-interconnect-check into .agents/skills/dynamo-interconnect-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-interconnect-check", 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 dynamo-interconnect-check -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills dynamo-interconnect-check --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/dynamo-interconnect-check .cursor/skills/dynamo-interconnect-check && 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 "dynamo-interconnect-check" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-interconnect-check into .cursor/skills/dynamo-interconnect-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-interconnect-check", 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/dynamo-interconnect-check--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 dynamo-interconnect-check -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills dynamo-interconnect-check --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/dynamo-interconnect-check .gemini/skills/dynamo-interconnect-check && 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 "dynamo-interconnect-check" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-interconnect-check into .gemini/skills/dynamo-interconnect-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-interconnect-check", 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 dynamo-interconnect-checkInstalls 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 dynamo-interconnect-check -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/dynamo-interconnect-check .github/skills/dynamo-interconnect-check && 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 "dynamo-interconnect-check" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-interconnect-check into .github/skills/dynamo-interconnect-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-interconnect-check", 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 dynamo-interconnect-check -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 dynamo-interconnect-check --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/dynamo-interconnect-check .opencode/skills/dynamo-interconnect-check && 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 "dynamo-interconnect-check" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-interconnect-check into .opencode/skills/dynamo-interconnect-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-interconnect-check", 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
dynamo-interconnect-check- GitHub stars
- 3.5k
- Used in
- 1 other repo
- Token cost
- ~1.6k tokens
- SKILL.md length
- 657 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 380
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Validate that a Dynamo deployment's NIXL/UCX/NCCL interconnect is ready for disaggregated serving over RDMA/NVLink.
- Works in 3 steps: Check Transport Env Vars On The Recipe → Check Node Capabilities → Validate NIXL Reachability
- Tasks that involve GPU and accelerator computing
- SKILL.md covers Purpose, Prerequisites, When To Use and Instructions, plus 7 more sections
- Runs Python scripts from its folder; calls python3 and kubectl
What it does
Dynamo Interconnect Check is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Validate that a Dynamo deployment's NIXL/UCX/NCCL interconnect is ready for disaggregated serving over RDMA/NVLink. Use after recipe-runner brings a deployment up (especially disagg/multi-node) to confirm the KV transport is correct; use troubleshoot for diagnosing already-failed pods.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `BENCHMARK.md`, `evals/evals.json` and `references/interconnect-env-vars.md`).
It sits in AI & LLM Engineering, covering GPU and accelerator computing and Deployment. 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.
When your agent uses it
- Tasks that involve GPU and accelerator computing
- Tasks that involve Deployment
Example prompts
- “/dynamo-interconnect-check”
Requirements
- Python 3
Workflow steps
3 steps, taken from the step headings in SKILL.md.
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
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3kubectl
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use kubectl, which can reach the network depending on how they are called.
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
Dynamo Interconnect Check loads about 1.6k tokens when it runs, and up to ~2.5k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 657 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); the scripts in this folder are not scanned.
SKILL.md
The full file from NVIDIA/skills at commit 0e0d506, republished under its Apache-2.0 licence (© NVIDIA). 657 words, ~1,599 tokens.
Download SKILL.mdSave it as
.claude/skills/dynamo-interconnect-check/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- dynamo-interconnect-check
- description
- Validate that a Dynamo deployment's NIXL/UCX/NCCL interconnect is ready for disaggregated serving over RDMA/NVLink. Use after recipe-runner brings a deployment up (especially disagg/multi-node) to confirm the KV transport is correct; use troubleshoot for diagnosing already-failed pods.
- license
- Apache-2.0
- metadata.author
- Dan Gil <dagil@nvidia.com>
- metadata.tags
- dynamo, nixl, rdma, disagg, validation
Dynamo Interconnect Check
<!--
SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
SPDX-License-Identifier: CC-BY-4.0
-->Purpose
Confirm that the transport disaggregated serving depends on actually works. A deployment can pass an endpoint smoke test while disagg is silently wrong: if NIXL/UCX cannot reach the peer worker over RDMA or NVLink, KV transfer falls back to a slow or broken path. Catch that with read-only checks before trusting a disagg deployment or its benchmark numbers.
This skill is read-only. It never mutates the cluster and never prints secrets.
Prerequisites
- Python 3.10+ on the operator machine.
kubectl execaccess to a worker pod in the target Dynamo deployment.- Read access to the recipe directory (
recipes/<model>/<framework>/<mode>). - For node-capability checks: tools like
ibstat,nvidia-smi,lsmodavailable in the worker pod image (missing tools are reported asskipped, not failures).
When To Use
- After
dynamo-recipe-runnerdeploys a disagg or multi-node recipe. - Before reporting disagg throughput/latency, so numbers reflect the real transport.
- When agg works but disagg is slow, hangs, or returns wrong output and you suspect the fabric rather than the model.
For diagnosing pods that are already crashing or unschedulable, use
dynamo-troubleshoot first.
Instructions
1. Check Transport Env Vars On The Recipe
python3 scripts/check_interconnect.py env recipes/<model>/<framework>/<mode>Reports which NIXL/UCX/NCCL transport variables are set and flags
disagg-critical ones (e.g. UCX_TLS, UCX_NET_DEVICES, NCCL_IB_HCA) that are
absent. Missing here is only a warning — they may be baked into the image — so
confirm with the node and NIXL checks. See
references/interconnect-env-vars.md for what each variable does.
2. Check Node Capabilities
Locally on a GPU node, or inside a running worker pod:
python3 scripts/check_interconnect.py node \
--namespace "${NAMESPACE}" --pod <worker-pod>Probes (read-only) for: InfiniBand devices and Active links, GPUDirect RDMA
(nvidia_peermem), GDRCopy, and NVLink in the GPU topology. Missing tools are
reported as skipped, not failures.
3. Validate NIXL Reachability
python3 scripts/check_interconnect.py nixl \
--namespace "${NAMESPACE}" --pod <worker-pod>Looks for NIXL test tooling in the pod and surfaces the exact next step to run a pairwise prefill↔decode transfer test. A full cross-pod transfer test requires two scheduled GPU pods on the fabric.
Available Scripts
| Script | Purpose | Arguments |
|---|---|---|
scripts/check_interconnect.py env | Inspect NIXL/UCX/NCCL env vars on a recipe | positional recipe path |
scripts/check_interconnect.py node | Probe InfiniBand, GPUDirect RDMA, GDRCopy, NVLink on a node or pod | --namespace, --pod |
scripts/check_interconnect.py nixl | Surface NIXL transfer-test readiness for a pod | --namespace, --pod |
Invoke via the agentskills.io run_script() protocol:
run_script("scripts/check_interconnect.py", args=["env", "recipes/qwen3-coder-480b/sglang/disagg"])
run_script("scripts/check_interconnect.py", args=["node", "--namespace", "dynamo-demo", "--pod", "qwen-worker-0"])Examples
Verify a disagg recipe's transport env shape before deploy:
python3 scripts/check_interconnect.py env recipes/qwen3-coder-480b/sglang/disaggAfter deploy, validate a worker pod's fabric:
python3 scripts/check_interconnect.py node \
--namespace dynamo-demo --pod qwen-worker-0
python3 scripts/check_interconnect.py nixl \
--namespace dynamo-demo --pod qwen-worker-0Equivalent through the agent protocol:
run_script("scripts/check_interconnect.py", args=["nixl", "--namespace", "dynamo-demo", "--pod", "qwen-worker-0"])Show full SKILL.md (275 more words)Show less
Output Contract
Each check returns ok / warn / fail / skipped with a one-line detail,
plus a rolled-up verdict on disagg transport readiness. Report:
- transport env vars present vs. disagg-critical ones missing
- RDMA / GPUDirect / NVLink capability status
- whether NIXL reachability was validated, and the next command if not
- a clear statement of whether disagg can be trusted, or what to fix first
Limitations
- Read-only fabric probe; does not run a full pairwise NIXL transfer (requires two scheduled GPU pods and the in-pod NIXL test tools).
skippedresults for missing tools (ibstat,nvidia-smi,lsmod) are inconclusive, not a pass.- Env-var check inspects the recipe text; values injected at runtime via initContainers or operator-applied envs are not detected.
- Single-node agg deployments do not exercise the transport — this skill is for disagg / multi-node validation.
Troubleshooting
| Symptom | Likely cause | Next step |
|---|---|---|
env reports all critical vars missing | Vars baked into image or injected by operator | Run the node check inside the worker pod to verify actual env |
node reports no Active IB link | Fabric down or HCA not provisioned to the node | Contact cluster admin; verify kubectl describe node shows nvidia.com/gpu and IB labels |
nvidia_peermem missing | GPUDirect RDMA module not loaded | Ask cluster admin to load nvidia-peermem; without it, NIXL falls back to staged copies |
nixl finds no test tools | Worker image lacks NIXL test harness | Use a NIXL-enabled image or run the standalone transfer test from a debug pod |
Benchmark
See BENCHMARK.md for the NVCARPS-EVAL performance report (auto-generated by the NVSkills CI pipeline). To refresh, re-run /nvskills-ci on an upstream PR touching this skill.
References
references/interconnect-env-vars.md— NIXL/UCX/NCCL env var catalog and IB capability checklist.- Use
scripts/check_interconnect.pyfor all read-only checks.
© 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 (scripts, references) in skills/dynamo-interconnect-check of NVIDIA/skills.
- SKILL.md
- BENCHMARK.md
- evals/evals.json
- references/interconnect-env-vars.md
- scripts/check_interconnect.py
- skill-card.md
- skill.oms.sig
Open the folder on GitHubat commit 0e0d506
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.
Compare with similar skills
Dynamo Interconnect Check 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 |
|---|---|---|---|---|---|---|
| Dynamo Interconnect Check this skillNVIDIA/skills | 3.5k | 1 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Cv DeployLMIXR/CV_Deployment_skill | 126 | — | ~547 | Automated safety check: Pass | None | |
| TensorRT-LLM InferenceOrchestra-Research/AI-Research-SKILLs | 13k | 5 repos | ~1.3k | 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 | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| Setup Workshopbrevdev/workshop-build-an-agent | 143 | — | ~2.3k | Automated safety check: Notes | Apache-2.0 |
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Related
Works with
Categories
Questions about Dynamo Interconnect Check
What does Dynamo Interconnect Check do?
Validate that a Dynamo deployment's NIXL/UCX/NCCL interconnect is ready for disaggregated serving over RDMA/NVLink. Dynamo Interconnect Check is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Validate that a Dynamo deployment's NIXL/UCX/NCCL interconnect is ready for disaggregated serving over RDMA/NVLink.
When should I use Dynamo Interconnect Check?
Dynamo Interconnect Check fits situations like: tasks that involve GPU and accelerator computing; tasks that involve Deployment.
How do I install Dynamo Interconnect Check in Claude Code?
Run `npx skills add NVIDIA/skills --skill dynamo-interconnect-check -a claude-code`. Or copy the skill folder (skills/dynamo-interconnect-check in NVIDIA/skills) into .claude/skills/dynamo-interconnect-check in your project. Claude Code loads it when a task matches its description.
How do I install Dynamo Interconnect Check in Codex?
Run `npx skills add NVIDIA/skills --skill dynamo-interconnect-check -a codex`. Or copy the skill folder (skills/dynamo-interconnect-check in NVIDIA/skills) into .agents/skills/dynamo-interconnect-check in your project. Codex loads it when a task matches its description.
Can I use Dynamo Interconnect Check 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 dynamo-interconnect-check -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dynamo-interconnect-check, .gemini/skills/dynamo-interconnect-check, .github/skills/dynamo-interconnect-check and .opencode/skills/dynamo-interconnect-check in your project.
What does Dynamo Interconnect Check need to run?
Going by SKILL.md and its folder, Dynamo Interconnect Check needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and kubectl). Our summary lists: Python 3.
Does Dynamo Interconnect Check 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 Dynamo Interconnect Check 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 Dynamo Interconnect Check use?
Dynamo Interconnect Check 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 Dynamo Interconnect Check use?
About 1.6k tokens (SKILL.md is roughly 6.4k 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 895 tokens, read only when the agent opens those files.
What are the alternatives to Dynamo Interconnect Check?
Skills that share tags, products or a category with Dynamo Interconnect Check: Cv Deploy (LMIXR/CV_Deployment_skill, 126 stars), TensorRT-LLM Inference (Orchestra-Research/AI-Research-SKILLs, 13k stars), Megatron-LM on SLURM (NVIDIA/Megatron-LM, 18k stars) and DGX Spark Memory and Thermal Ops (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Dynamo Interconnect Check?
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.