Agent skill

cuopt-multi-objective-exploration

Trace, complete, and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).

NVIDIAgithub.com/NVIDIAGitHub ↗
claude-codecodexApache-2.0
Install
npx skills add NVIDIA/skills --skill cuopt-multi-objective-exploration --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 5
SKILL.md size: 15 KB
Bundled scripts: none
Version: 26.08.00
Declared author: NVIDIA cuOpt Team
Path: skills/cuopt-multi-objective-exploration/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,789
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Multi-Objective Exploration cuOpt optimizes **one** objective per solve. Many real problems have several objectives that pull against each other — cost vs. service level, return vs. risk, makespan vs. overtime, distance vs. vehicle count. A single solve answers "what's optimal *for one particular weighting*," but it hides the tradeoff the user actually needs to see. This skill turns a sequence o

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About this skill
What does the cuopt-multi-objective-exploration skill do?

Trace, complete, and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).

How do I install it?

Run `npx skills add NVIDIA/skills --skill cuopt-multi-objective-exploration --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From NVIDIA/skills, a repository with 2,789 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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