cuPyNumeric Migration Readiness Agent Skill

Pre-migration readiness assessor for porting NumPy to cuPyNumeric.

Context cost
56.2k tokensestimated from the bundle, loaded when it triggers
Bundle
39 files · 289.9 kB24 scripts among them — read before you run
Licence
CC-BY-4.0 OR Apache-2.0the author’s own terms
Last change
—v2.0.0
Servers it uses
Noneruns standalone

What it does

Pre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host…

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

data science

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md18.4 kB · preview
--- name: cupynumeric-migration-readiness license: CC-BY-4.0 OR Apache-2.0 compatibility: Knowledge-driven assessment; no cuPyNumeric install required. Runtime claims target Linux x86_64/aarch64 with NVIDIA compute capability >= 7.0 and CUDA 12.x/13.x. Runtime validation is delegated to cuPyNumeric Doctor. metadata: author: "NVIDIA Corporation <legate@nvidia.com>" version: "2.0.0" tags: - cupynumeric - legate - numpy - gpu - distributed-computing upstream: https://github.com/nv-legate/cupynumeric docs: https://docs.nvidia.com/cupynumeric/latest/ ---
19# cuPyNumeric Migration Readiness
20
21## Purpose
22
23**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.
24
25**This is a static, read-only assessment.** Inspect the user's source with Read, Grep, and Glob. Do **not** execute the user's code, modify or write files, or print environment variables or secrets. The legate, and cuPyNumeric Doctor commands shown below are suggestions for the *user* to run — not actions this skill performs.
26
27If this skill has never been seen before, head to [references/getting-started.md](references/getting-started.md) first.
28
29## When to use this skill
30
31Use when the user is **about to** migrate NumPy code to GPU and asks whether it will scale on cuPyNumeric / GPU, whether they should migrate, which parts will benefit, what must change before porting, or whether the port is worth it — or mentions pre-port assessment, scaling analysis, idiom analysis, GPU refactor planning, or identifying NumPy anti-patterns for GPU.
32
33**Decline and redirect** when the request is *not* a pre-migration assessment:
34
35- **Post-migration performance / profiling** ("already ported, why is it slow?") → point to legate --profile and the upstream [profiling and debugging](https://docs.nvidia.com/cupynumeric/latest/user/profiling_debugging.html) walkthrough.
36- **Custom CUDA / kernel authoring** ("write/optimize a CUDA kernel")
37
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md2,301 words
Files39
LicenceCC-BY-4.0 OR Apache-2.0
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈350
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
55,850
on trigger
The instruction body and 38 supporting files, read only when the skill fires.
28.1%
of a 200k window
Ten skills this size would not fit in the window together.
050k100k150k200k context window

56.2k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

39 files, 289.9 kB on disk. Mostly text — the instructions the model reads — with 24 scripts in it that your client would run only if the instructions tell it to.

  • assets/api-support.md12.7 kB
  • assets/examples/blocks_scaling.py2.9 kB
  • assets/examples/needs_refactor.py2.2 kB
  • assets/examples/scales_well.py2.1 kB
  • assets/sample_report.md12.6 kB
  • BENCHMARK.md3.5 kB
  • evals/evals.json55.9 kB
  • evals/files/api_gap_hotpath.py1.5 kB
  • evals/files/blocks_scaling.py2.5 kB
  • evals/files/convergence_loop.py1.2 kB
  • evals/files/cupy_mixed.py1.0 kB
  • evals/files/dense_linalg.py1.6 kB
  • evals/files/dense_with_scipy_boundary.py1.8 kB
  • evals/files/graph_workload.py1.6 kB
  • evals/files/item_sync.py1.3 kB
  • evals/files/jacobi_heat.py1.0 kB
  • evals/files/many_blocks.py1.4 kB
  • evals/files/monte_carlo_bs.py1.2 kB
  • evals/files/monte_carlo_good.py1.5 kB
  • evals/files/needs_refactor.py1.6 kB
  • evals/files/scales_well.py1.8 kB
  • evals/files/sequential_recurrence.py1.3 kB
  • evals/files/sparse_sklearn.py1.5 kB
  • evals/files/tiny_array.py1.6 kB
  • evals/files/unlisted_api.py1.8 kB
  • evals/files/view_mutation.py0.8 kB
  • references/case-studies.md13.7 kB
  • references/decision-framework.md9.5 kB
  • references/execution-model.md9.6 kB
  • references/getting-started.md7.4 kB
  • references/gpu-stack.md14.8 kB
  • references/idioms-that-block.md22.9 kB
  • references/idioms-that-scale.md13.8 kB
  • references/partitioning-and-balance.md11.8 kB
  • references/refactor-recipes.md13.4 kB
  • scripts/fetch_api_support.py19.5 kB
  • scripts/tests/test_fetch_api_support.py10.4 kB
  • SKILL.md18.4 kB
  • skill-card.md4.8 kB
What is not in it

A skill installs nothing and depends on nothing: it is a folder your client reads. This one carries 24 scripts beside the text, so the bundle is 39 files you can review in full before installing. The CC-BY-4.0 OR Apache-2.0 licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# cuPyNumeric Migration Readiness · 56.2k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/cupynumeric-migration-readiness/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/cupynumeric-migration-readiness" ] && { [ ! -e .claude/skills/cupynumeric-migration-readiness ] || { mv .claude/skills/cupynumeric-migration-readiness "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/cupynumeric-migration-readiness" .claude/skills/ && echo "Installed .claude/skills/cupynumeric-migration-readiness"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add nvidia/cupynumeric-migration-readiness

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/cupynumeric-migration-readiness/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/cupynumeric-migration-readiness/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/cupynumeric-migration-readiness" ] && { [ ! -e ~/.claude/skills/cupynumeric-migration-readiness ] || { mv ~/.claude/skills/cupynumeric-migration-readiness "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/cupynumeric-migration-readiness" ~/.claude/skills/ && echo "Installed ~/.claude/skills/cupynumeric-migration-readiness" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/cupynumeric-migration-readiness/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Version2.0.0
Publishedno release date on file
PriceFree
Referencenvidia/cupynumeric-migration-readiness

Versions

v2.0.0 is what is on the shelf; no release here carries a date. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v2.0.0
  • No earlier releases have been published to the marketplace.
Pinning

The install command always fetches the release that is current the day you run it — v2.0.0 today — and cannot ask for an earlier one. The copy on your disk does not change until you run it again.

Reviews

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