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/cuopt-developer

@e37c0a0
by NVIDIA Corporationnvidia/skills3.5k stars
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Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.

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Use this Skill: https://skilld.dev/gh/nvidia/skills/cuopt-developer

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referencesfirst_time_setup.md

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First-Time Dev Environment Setup

Read this when a contributor is setting up the cuOpt dev environment for the first time — clone, conda env, initial build, initial test run. Once that's working, the rest of cuopt-developer (build/test commands, conventions, contribution workflow) takes over.

Required questions

Ask these before issuing commands:

  1. OS and GPU — Linux? Which CUDA version does the GPU driver support (run nvidia-smi, top-right "CUDA Version")?
  2. Goal — Contributing upstream, or local fork/modification?
  3. Component — C++/CUDA core, Python bindings, server, docs, or CI?

The component answer scopes which part of the codebase to read first and which build target to use (e.g. ./build.sh libcuopt vs ./build.sh cuopt).

Setup walk-through (conceptual)

  1. Clone the cuOpt repo (and submodules, if any). If the machine has no conda yet, bootstrap miniforge into the user's home directory first (no sudo — user-space install only).
  2. Pre-flight checks — CUDA driver compatibility, conda env creation + activation, PARALLEL_LEVEL, dataset setup. Creating the env from conda/environments/all_cuda-*.yaml is allowed and expected here, not something to hand off to the user. Walk through these before the first build using SKILL.md → Pre-flight Checks. Skipping any of them surfaces as confusing build- or runtime errors later.
  3. First build — once the env is active, run ./build.sh (or a component-scoped variant). Targets and PARALLEL_LEVEL tuning live in build_and_test.md.
  4. First test run — fetch datasets per CONTRIBUTING.md first, then run the C++/Python test suites from build_and_test.md. A passing build + test confirms the env is wired up correctly.
  5. Optional — pre-commit install to run style checks on every git commit (see contributing.md).

Use the repo's README and CONTRIBUTING.md as the canonical source for exact versions and any deviations.

After setup

Once ./build.sh and the test suites succeed, the env is verified. From here, ongoing build/test/debug/contribute work is covered by the rest of cuopt-developer:

Source: SKILL.md on GitHub

Third-party checks

1 alert3mo3 checks · Risk SAFE
  • Gen Agent Trust Hub3mo

    The cuopt-developer skill is a comprehensive and secure development environment guide for the NVIDIA cuOpt project. It incorporates robust safety guardrails, including explicit prohibitions against privileged operations (sudo), system-level modifications, and insecure coding practices such as the use of 'eval()' on user input or remote script execution via 'curl | bash'. The skill emphasizes reproducible, user-space environment management using conda and standard project tools.

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  • Snyk3mo

    Risk: CRITICAL · 1 issue

Provenance

Signed by skilld at e37c0a0. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 3 months ago

Capability

version
26.08.00
Other metadata
metadata
{
  "author": "NVIDIA cuOpt Team",
  "tags": [
    "cuopt",
    "development",
    "contributing",
    "cpp-cuda",
    "python-bindings"
  ]
}

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