cuPyNumeric Migration Readiness

cuPyNumeric Migration Readiness is a Quality skill for Claude Code, published by NVIDIA in skills.

3K stars345 forkson NVIDIA/skillsAdded 2026/08/17+3% in starsRepository updated 2026/08/17

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Install in seconds

Install cuPyNumeric Migration Readiness

Copy cuPyNumeric Migration Readiness into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/NVIDIA/skills/tree/main/skills/cupynumeric-migration-readiness ~/.claude/skills/cupynumeric-migration-readiness

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/NVIDIA/skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/cupynumeric-migration-readiness/SKILL.md in NVIDIA/skills
Installs to: ~/.claude/skills/cupynumeric-migration-readiness
Collection: One of 25 skills cataloged from this repository
Category: Quality — 1354 skills

What cuPyNumeric Migration Readiness does

cuPyNumeric Migration Readiness assesses NumPy code before porting to cuPyNumeric, identifying which APIs will scale on GPU and which need refactoring. Use it before starting a migration to get a verdict and concrete refactor pointers.

cuPyNumeric Migration Readiness is cataloged under Quality on DirSkills. cuPyNumeric Migration Readiness comes from a repository tagged agent-skills, agentic-ai, ai-agents, claude-code and codex.

Documentation

README

Excerpt

cuPyNumeric Migration Readiness

Purpose

Use this skill BEFORE the migration, not during. Answer one question: which of the user's existing NumPy APIs will scale on cuPyNumeric, and which need refactoring, before they commit engineer-weeks to porting? To answer it: read the source, classify each NumPy idiom by its expected multi-GPU scaling on the Legate/NVIDIA GPU stack, cross-reference the bundled API-support manifest, and produce a structured verdict with per-finding reasoning and recipe pointers.

This is the opening of the README. Read the full README on GitHub.

Frequently asked about cuPyNumeric Migration Readiness

What else does NVIDIA publish alongside cuPyNumeric Migration Readiness?
cuPyNumeric Migration Readiness is one of 25 skills that DirSkills catalogs from NVIDIA/skills, the repository it ships in. Its siblings there include AIQ Deploy, AIQ Research and AMC RTSP Calibration. Each one is a separate skill with its own page in this directory, installs the same way cuPyNumeric Migration Readiness does, and is maintained by NVIDIA in that same repository. The rest of the collection is listed on the NVIDIA/skills page.
How does cuPyNumeric Migration Readiness compare to other Quality skills?
cuPyNumeric Migration Readiness ranks #452 by stars among the 1354 Quality skills in this catalog. The most-starred ones next to it are Benchmark, Benchmark Optimization Loop and API Design Patterns. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of cuPyNumeric Migration Readiness against them. Open each page to compare what they document and how they install.