Best for
- Use when the user asks to "deploy on REPLACE-PLATFORM", "run on REPLACE-PLATFORM", or mentions the platform's distinctive concepts (e.
NVIDIA-TAO/tao-skill-bank/templates/skill-skeleton/platform/SKILL.md
Where and how GPU jobs run on this platform. One-to-three-sentence summary. Use when the user asks to "deploy on REPLACE-PLATFORM", "run on REPLACE-PLATFORM", or mentions the platform's distinctive concepts (e.g., resource shape, instance, node group).
Decision brief
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).
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/NVIDIA-TAO/tao-skill-bank --skill "templates/skill-skeleton/platform"Inspect the Agent Skill "REPLACE-WITH-PLATFORM-NAME" from https://github.com/NVIDIA-TAO/tao-skill-bank/blob/ae5e99c2148cf6bab95d150ee243a6da3f2c1fb1/templates/skill-skeleton/platform/SKILL.md at commit ae5e99c2148cf6bab95d150ee243a6da3f2c1fb1. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
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…
Review the “Docker-native workflow” section in the pinned source before continuing.
Review the “External dependencies” section in the pinned source before continuing.
Review the “Authentication” section in the pinned source before continuing.
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 85/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 82 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Standalone install? If this session was not initialized by the TAO skill bank plugin, run the
tao-setupskill 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.
| Dependency | Purpose | Install |
|---|---|---|
<cli-name> | Submit jobs / manage resources | <install-command> |
| 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 |
# 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
<platform-cli> exec <target> -- docker run --gpus all --rm \
-e <env-vars> \
-v <host-path>:<container-path> \
nvcr.io/... \
<command>
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.
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.PENDING RUNNING COMPLETE ERROR CANCELED UNKNOWN.mark ... --state CANCELED.| Symptom | Cause | Fix |
|---|---|---|
<error> | ... | ... |
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