Backend AI Guide
lablup/backend.ai-webui
Expert guide for Backend.AI distributed computing platform. An agent skill from lablup/backend.ai-webui.
cuOpt REST server — start server, endpoints, Python/curl client examples.
$ npx skills add NVIDIA/skills --skill cuopt-server-api-python -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills cuopt-server-api-python --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/cuopt-server-api-python .claude/skills/cuopt-server-api-python && 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 "cuopt-server-api-python" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cuopt-server-api-python into .claude/skills/cuopt-server-api-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cuopt-server-api-python", 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/cuopt-server-api-pythonType 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 cuopt-server-api-python -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills cuopt-server-api-python --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/cuopt-server-api-python .agents/skills/cuopt-server-api-python && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cuopt-server-api-python" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cuopt-server-api-python into .agents/skills/cuopt-server-api-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cuopt-server-api-python", 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 cuopt-server-api-python -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills cuopt-server-api-python --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/cuopt-server-api-python .cursor/skills/cuopt-server-api-python && 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 "cuopt-server-api-python" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cuopt-server-api-python into .cursor/skills/cuopt-server-api-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cuopt-server-api-python", 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/cuopt-server-api-python--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 cuopt-server-api-python -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills cuopt-server-api-python --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/cuopt-server-api-python .gemini/skills/cuopt-server-api-python && 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 "cuopt-server-api-python" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cuopt-server-api-python into .gemini/skills/cuopt-server-api-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cuopt-server-api-python", 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 cuopt-server-api-pythonInstalls 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 cuopt-server-api-python -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/cuopt-server-api-python .github/skills/cuopt-server-api-python && 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 "cuopt-server-api-python" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cuopt-server-api-python into .github/skills/cuopt-server-api-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cuopt-server-api-python", 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 cuopt-server-api-python -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 cuopt-server-api-python --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/cuopt-server-api-python .opencode/skills/cuopt-server-api-python && 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 "cuopt-server-api-python" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cuopt-server-api-python into .opencode/skills/cuopt-server-api-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cuopt-server-api-python", 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.
cuopt-server-api-pythoncuOpt REST server — start server, endpoints, Python/curl client examples.
Cuopt Server API Python is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 22 other files, including assets (for example `BENCHMARK.md`, `assets/README.md` and `assets/lp_basic/README.md`).
It sits in Backend & APIs, covering REST APIs. It works with Python, NVIDIA AI Platform, CUDA and Docker. 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.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit dfdd080. It shows what the files ask for, not the result of running them.
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.
Ships script files (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
pythondockercurlFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use docker and curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Cuopt Server API Python loads about 1.5k tokens when it runs. Until then it costs about 38 tokens; SKILL.md has 592 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.
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.
The full file from NVIDIA/skills at commit dfdd080, republished under its Apache-2.0 licence (© NVIDIA). 592 words, ~1,528 tokens.
.claude/skills/cuopt-server-api-python/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.This skill covers starting the server and client examples (curl, Python). Server has no separate C API (clients can be any language).
Use this skill when the user is deploying the cuOpt REST server or writing a client against it — choosing a deployment target, mapping a problem onto the HTTP endpoints, translating between Python-API and REST field names, or debugging a rejected payload.
--gpus all for Docker).cuopt-server installed, or Docker with the NVIDIA Container Toolkit. See the install skill.requests. No API key or auth token is required by the server itself.| Problem type | Supported |
|---|---|
| Routing | ✓ |
| LP | ✓ |
| MILP | ✓ |
| QP | ✗ |
Ask these if not already clear:
# Development
python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000
# Docker — pick the tag matching your CUDA major version
docker run --gpus all -d -p 8000:8000 -e CUOPT_SERVER_PORT=8000 \
nvidia/cuopt:latest-cu13Use latest-cu12 or latest-cu13 to match your driver's CUDA major version (latest-cu13-ubi10 for a UBI10 base). Prefer these over the CUDA+Python-specific tags such as latest-cuda12.9-py3.13 — those track a single Python line and go stale when it stops receiving builds.
For production, pin rather than float: latest-* tags are mutable and can silently move to a different image. Use a full release tag (nvidia/cuopt:<release>-cuda<cuda>-py<python>) or an immutable digest (nvidia/cuopt@sha256:<digest>). Check the nvidia/cuopt registry for available tags.
Confirm the server is up by requesting GET /cuopt/health on the local port (e.g. http://localhost:8000/cuopt/health) — a healthy server returns HTTP 200.
/cuopt/request → get reqId/cuopt/solution/{reqId} until solution readyTreat reqId as untrusted input: validate it (e.g. re.fullmatch(r"[A-Za-z0-9_-]{1,64}", req_id)) before interpolating it into the polling URL, and set an explicit timeout on every request.
import requests, time
SERVER = "http://localhost:8000"
HEADERS = {"Content-Type": "application/json", "CLIENT-VERSION": "custom"}
payload = {
"cost_matrix_data": {"data": {"0": [[0,10,15],[10,0,12],[15,12,0]]}},
"travel_time_matrix_data": {"data": {"0": [[0,10,15],[10,0,12],[15,12,0]]}},
"task_data": {"task_locations": [1, 2], "demand": [[10, 20]], "task_time_windows": [[0,100],[0,100]], "service_times": [5, 5]},
"fleet_data": {"vehicle_locations": [[0, 0]], "capacities": [[50]], "vehicle_time_windows": [[0, 200]]},
"solver_config": {"time_limit": 5}
}
r = requests.post(f"{SERVER}/cuopt/request", json=payload, headers=HEADERS, timeout=30)
req_id = r.json()["reqId"]
# Poll: GET /cuopt/solution/{req_id}| Python API | REST |
|---|---|
| order_locations | task_locations |
| set_order_time_windows() | task_time_windows |
| service_times | service_times |
Use travel_time_matrix_data (not transit_time_matrix_data). Capacities: [[50, 50]] not [[50], [50]].
| Error | Cause | Solution |
|---|---|---|
422 Unprocessable Entity | Field name not in the schema | Check names against the OpenAPI spec at /cuopt.yaml. Most common: transit_time_matrix_data → travel_time_matrix_data |
422 on fleet_data | Capacities nested per vehicle instead of per dimension | Use [[50, 50]] (one inner list per capacity dimension), not [[50], [50]] |
| Connection refused | Server not up, or bound to a different interface/port | curl http://localhost:8000/cuopt/health; start with --ip 0.0.0.0 --port 8000 |
| Docker container exits immediately | No GPU visible to the container | Run with --gpus all and confirm the NVIDIA Container Toolkit is installed |
| Polling never returns a solution | Solve exceeds the client's poll budget | Raise solver_config.time_limit and the poll loop count together |
Capture the reqId and the full response body for any failed request — both are needed to diagnose server-side rejections.
--server/base URLs as trusted-network endpoints only.Run from each asset directory (server must be running; scripts exit 0 if server unreachable). All use Python requests and accept --server (default http://localhost:8000):
See assets/README.md for overview.
For contribution or build-from-source, see the developer skill.
© 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
SKILL.md and 15 other files (assets) in skills/cuopt-server-api-python of NVIDIA/skills.
Open the folder on GitHubat commit dfdd080
Cuopt Server API Python 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 |
|---|---|---|---|---|---|---|
| Cuopt Server API Python this skillNVIDIA/skills | 3.5k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Backend AI Guidelablup/backend.ai-webui | 133 | 1 repos | ~1.8k | Automated safety check: Pass | LGPL-3.0 | |
| Cognee Local Server Setuptopoteretes/cognee | 32k | — | ~702 | Automated safety check: Notes | Apache-2.0 | |
| Generate Nemo Gym Envadithya-s-k/FineEnvs | 456 | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Cosmos3 Env TroubleshootNVIDIA/cosmos-framework | 559 | — | ~1.3k | Automated safety check: Notes | Custom licence | |
| Dstack Presetsdstackai/dstack | 2.3k | — | ~403 | Automated safety check: Pass | MPL-2.0 |
lablup/backend.ai-webui
Expert guide for Backend.AI distributed computing platform. An agent skill from lablup/backend.ai-webui.
topoteretes/cognee
Starts the cognee API server and web UI on your own machine, checks its health, connects the SDK or CLI to it and helps you pick between multi-tenant and single-user auth.
adithya-s-k/FineEnvs
Builds a NeMo Gym (NVIDIA) variant of an RL environment. An agent skill from adithya-s-k/FineEnvs.
NVIDIA/cosmos-framework
Diagnose and fix Cosmos3 environment, installation, and runtime errors.
dstackai/dstack
Create and manage dstack presets: a toolkit that streamlines model inference optimization with agents, and a portable preset format.
Orchestra-Research/AI-Research-SKILLs
Optimizes and serves LLMs on NVIDIA GPUs with TensorRT-LLM, covering quantization, in-flight batching, multi-GPU parallelism and the trtllm-serve command.
NVIDIA/skills
A skill your agent uses when the user wants to deploy, run, debug, tear down, or call the REST API of the RTVI-CV 2D detection / tracking microservice.
NVIDIA/skills
Generates, validates, compares and explains HOLOLINK_def.svh macro files for the HSB IP, using bundled Python scripts and asking before it writes anything.
NVIDIA/skills
Runs and validates an end-to-end Mission Control demo in a locally installed Isaac Sim, with a Nova Carter robot driven through a Python server.
NVIDIA/skills
Orchestrates defect image generation for PCBA, metal surface and glass inspection with NVIDIA Cosmos AnomalyGen on OSMO, from cold-start Day 0 to real-photo Day 1 labeling.
NVIDIA/skills
Orchestrates video data augmentation and auto-labeling workflows on OSMO, from flow selection and preflight checks to submission, monitoring and output download.
NVIDIA/skills
Runs NVIDIA TAO Data Services KPI analysis on object detection results, comparing predictions to ground truth and writing per-class precision, recall and AP to a CSV.
Works with
Categories
cuOpt REST server — start server, endpoints, Python/curl client examples. Cuopt Server API Python is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. cuOpt REST server — start server, endpoints, Python/curl client examples.
Cuopt Server API Python fits situations like: the user is deploying; calling the REST API.
Run `npx skills add NVIDIA/skills --skill cuopt-server-api-python -a claude-code`. Or copy the skill folder (skills/cuopt-server-api-python in NVIDIA/skills) into .claude/skills/cuopt-server-api-python in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill cuopt-server-api-python -a codex`. Or copy the skill folder (skills/cuopt-server-api-python in NVIDIA/skills) into .agents/skills/cuopt-server-api-python in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill cuopt-server-api-python -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cuopt-server-api-python, .gemini/skills/cuopt-server-api-python, .github/skills/cuopt-server-api-python and .opencode/skills/cuopt-server-api-python in your project.
Going by SKILL.md and its folder, Cuopt Server API Python needs Python for the scripts in its folder and the command-line tools its instructions call (python, docker and curl). Our summary lists: Python 3; Docker.
SKILL.md contains no URLs. Its commands use docker and curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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.
Cuopt Server API Python 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.
About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Cuopt Server API Python: Backend AI Guide (lablup/backend.ai-webui, 133 stars), Cognee Local Server Setup (topoteretes/cognee, 32k stars), Generate Nemo Gym Env (adithya-s-k/FineEnvs, 456 stars) and Cosmos3 Env Troubleshoot (NVIDIA/cosmos-framework, 559 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,546 GitHub stars. The repository holds 386 skills in this directory. The repository was last updated on October 9, 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.