What is REPLACE-WITH-PLATFORM-NAME?

A template for documenting how GPU jobs run on a particular computing platform. It covers the platform's execution model, command-line setup, authentication, environment variables, checks, and quick starts.

Use it to document platform-specific GPU deployment instructions, including installation, login, preflight checks, and Docker-based workflows.

It gives developers a consistent way to explain how to submit and manage GPU workloads on a platform.

REPLACE-WITH-PLATFORM-NAME — Skill for Claude Code by NVIDIA-TAO

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add NVIDIA-TAO/tao-skill-bank --skill platform

Clone the repo

git clone --depth 1 https://github.com/NVIDIA-TAO/tao-skill-bank

Made for: Claude Code.

Or install tao-skill-bank, the plugin that ships this one along with the rest of its 85 skills, 1 hook.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/platform/github.svg)](https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/platform)

Your own site

<a href="https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/platform"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/platform/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/platform"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/platform.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 795 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium MCP Rug Pull · line 60
Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.

Fix: Pin the image: image:tag or image@sha256:abc123

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00070	$0.00795
Opus 5	$0.00035	$0.00398
Sonnet 5	$0.00014	$0.00159
Haiku 4.5	$0.00007	$0.00080

Measured 7d ago against content hash d9fb1cda8568, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

REPLACE-WITH-PLATFORM-NAME scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

templates/skill-skeleton/platform/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Platform Name

Standalone install? If this session was not initialized by the TAO skill bank plugin, run the tao-setup skill first (host preflight, credentials, cross-skill discovery).

Short summary of the platform's execution model. Instance-based or job-based? API-first or docker-first? Single-node or multi-node? Managed or self-hosted?

For generic docker conventions, defer to tao-skill-bank:tao-run-on-docker. This skill covers the platform-specific layering on top.

External dependencies

Dependency	Purpose	Install
`<cli-name>`	Submit jobs / manage resources	`<install-command>`

Authentication

Method	When to use
API token (recommended)	Scripted / automated workflows
Browser login	Interactive development

Env vars:

Env var	Required	Purpose
`<PLATFORM>_API_TOKEN`	Yes (or manual login)	API auth

Preflight

# 1. CLI installed
which <cli-name> || echo "MISSING: install from <url>"

# 2. Logged in
<cli-name> ls >/dev/null 2>&1 || echo "NOT LOGGED IN"

# 3. Platform-specific checks

Quick start

Docker-native workflow

<platform-cli> exec <target> -- docker run --gpus all --rm \
  -e <env-vars> \
  -v <host-path>:<container-path> \
  nvcr.io/... \
  <command>

Execution — the four verbs

A platform skill is a consumer: it runs a model/data skill's spec-bundle by implementing submit/status/logs/cancel over the native CLI, mutating only the job-record. No SDK. See tao-skill-bank:tao-launch-workflow for the shared contract and tao-skill-bank:tao-run-on-docker for a worked example.

submit — stage inputs via tao-data-io, lint the command with redact_secrets.py, then tao_job_record.py open (mints the id + binds results_dir before launch), launch naming the backend object after the id, and mark ... --state RUNNING.
status / logs — poll the native backend; map states to the fixed vocab PENDING RUNNING COMPLETE ERROR CANCELED UNKNOWN.
cancel — native cancel + teardown, then mark ... --state CANCELED.

Read the full file on GitHub · 93 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

7d ago First seen · 93 lines · 70 tokens per session scan A d9fb1cda8568

Subscribe to this mod's changes

REPLACE-WITH-PLATFORM-NAME is a skill published in the GitHub repository NVIDIA-TAO/tao-skill-bank (88 stars, last pushed yesterday), licensed Apache-2.0. It adds 70 tokens to every session and 795 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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