gpu-first-guidance
Use when recommending how to run a workbench workload, writing user-facing docs, or answering "what should I run first?" — lead with the Nebius GPU path and…
Skill by nebius
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/nebius-gpu-first-guidance
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: ml, writing, sales
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/gpu-first-guidance
What's inside
- Skill name
gpu-first-guidance- Description
- Use when recommending how to run a workbench workload, writing user-facing docs, or answering "what should I run first?" — lead with the Nebius GPU path and keep hosted-inference options framed as what they are, rather than as ways to avoid GPUs.
- License
- Apache-2.0
- Instructions
- 109 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Lead with the GPU path (kindly) Nebius Physical AI exists to run real physical-AI work on Nebius AI Cloud GPUs. When someone asks what to run, the helpful answer is the one that gets them to a real result on real hardware. This skill is about **emphasis and framing**, not about withholding anything. Be accurate, be generous, and never make someone feel awkward for asking about cost or for having no cluster yet. ## The habit When you recommend a path, order it like this: 1. **Lead with the GPU workload** the user actually wants — a robot guide, a Cosmos run, a training job, the Physical AI Data Factory. 2. **Name the real prerequisite** plainly: a configured project and a GPU cluster. `npa provision-if-absent` gets them there. 3. **Mention hosted inference when it fits the workload**, described by what it does, not by what it avoids. Before presenting a checked-in tool command as runnable, resolve or preflight its image. A publication-quarantined default is not a recommendation even when the old registry tag still pulls. Lead with the intended GPU path, then state that execution currently requires a separately scanned immutable image override or must wait for a repaired accepted release; never tell an operator to bypass the quarantine with the stale tag. What changes is the headline, not the truth. If a user's workload genuinely is hosted inference, recommending Token Factory is simply the right answer. ## Language | Prefer | Instead of | | --- | --- | | "Run it on an L40S — here's the command" | "You can skip the GPU entirely" | | "Hosted inference through Token Factory" | "Zero-GPU / no-GPU / no-cluster path" | | "Check credentials first with `health preflight`" | "Before you burn GPU-hours" | | "This stage runs on hosted inference" | "This stage is free" | | "Start with the Franka guide" | "Start with the one that needs no GPU" | The right-hand column is not forbidden vocabulary — it is framing that quietly positions GPU time as waste. That framing is what to drop. ## Token Factory has a real job [Nebius Token Factory](../../../docs/workbench/token-factory.md) is a genuine hosted-inference product: captioning, batch generation, and Cosmos physical-AI reasoning. Describe it that way. - **Do** recommend it for captioning, judging, and reasoning stages — including as part of a larger GPU pipeline, which is the common case. - **Do** be straightforward that it needs a `NEBIUS_TOKEN_FACTORY_KEY` and no cluster, when a user asks what it requires. - **Avoid** presenting it as the recommended first step *because* it dodges provisioning, or as a substitute for the GPU workload someone came to run. See also `skills/tools/token-factory/SKILL.md`. ## When someone asks for a GPU-free path anyway Help them. Cheerfully. People have real constraints: an approval still pending, a quota request in flight, a laptop on a plane, a CI job that must not provision. Answer the question they asked, completely and without a lecture. - Give the working answer first. - Note the GPU path **once**, as an invitation rather than a correction — for example, "when your cluster is ready, the Franka guide picks up from here." - Do not repeat the nudge, moralize about spend, or imply they are doing it wrong. A user who feels sold to stops asking questions. A user who gets a straight answer comes back for the GPU run. ## Writing docs and READMEs - Do not add "no GPU required" as a selling point, a guide title, or a table column. - Do not add sections whose premise is minimizing GPU usage. - Keep operational guidance — GPU routing, accelerator naming, image pull failures — but frame it as *getting your run to work*, not as *avoiding waste*. That content lives in [known-footguns.md](../../../docs/workbench/troubleshooting/known-footguns.md). - Leave validation evidence alone. Test matrices record what was exercised, including local and stub backends; they are records, not recommendations, and editing them for tone would make them wrong. ## Gotchas - **Accuracy outranks emphasis.** Never claim a stage needs a GPU when it does not, and never quote a GPU requirement you have not checked. Overselling is a worse failure than a stray "zero-GPU". - **`--dry-run`, `--plan-only`, and `stub` backends are still fine to recommend.** They are development and validation tools, not a GPU-free product path. Recommend them for what they are: a way to check a spec before it runs. - **Cost questions deserve real answers.** If someone asks what a run costs, answer it. Point at preemptible capacity ([preemptible-vms.md](../../../docs/workbench/preemptible-vms.md)) and right-sizing rather than steering them off GPUs altogether. ## Verify ```bash npa/.venv/bin/python -m pytest npa/tests/guardrails/test_skills_index.py -q ```
From nebius/nebius-physical-ai, Apache-2.0.
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Signals
- Stars
- 60
- Forks
- 19
- Open issues
- 10
- Last commit (this folder)
- Oct 1, 2026 (27 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/nebius/nebius-physical-ai
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Use when working on Cosmos world model serving, inference, serverless training smoke validation, backend selection, or rendering limitations.
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Cite this page
gpu-first-guidance skill. Agent Mart. https://agentmart.dev/skills/nebius-gpu-first-guidance (last updated 2026-10-24)