Agent skill · software engineering · nvidia
tao-run-on-docker
The Docker execution platform for TAO jobs — a local daemon or a remote GPU box via DOCKER_HOST=ssh://user@host. Implements the four-verb consumer contract (submit/status/logs/cancel) over the docker CLI, wired to the job-record, tao-data-io staging, and the redact lint, on top of the underlying docker conventions (--gpus, mounts, NGC auth, inspection, data-root relocation, error modes). Use to run any single-node TAO container action on Docker without the SDK. Trigger keywords — docker, docker run, run on docker, DOCKER_HOST, remote docker, nvcr.io, --gpus, single-node GPU job.
Why this skill is useful
Provides specific Docker commands and patterns for running NVIDIA GPU workloads that the AI wouldn't reliably generate on its own.
What it needs
Requires docker installed locally. Requires ngc account access. About 11k tokens when loaded. Last updated 2026-08-07. 2,816 stars on the source repository.
What this skill does
Docker for NVIDIA GPU Workloads 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). The Docker execution platform: a consumer that runs a model/data skill's spec-bundle by implementing four verbs (submit/status/logs/cancel) over the docker CLI, on a local daemon or a remote GPU box via DOCKERHOST=ssh://. The verbs (§ Execution) sit on top of the docker conventions in the rest of this file — GPU flags, mounts, NGC auth, inspection, error modes — which are the how the model/data skill defers to. Single-node only; for multi-node use SLURM or Kubernetes. Sources: official Docker CLI reference (<https://docs.docker.com/reference/cli/docker/>) and NVIDIA Container Toolkit docs. Prerequisites 1. Host GPU runtime — by default, NVIDIA driver >=580, CUDA Toolkit >=13.0, and NVIDIA Container Toolkit >=1.19.0. If the selected model's references/skillinfo.yaml declares runtimerequirements.gpuhost, pass those values to tao-setup-nvidia-gpu-host instead. Model requirements override the defaults for that workflow. 2. Docker — docker --version must return ≥ 20.10. Install: <https://docs.docker.com/engine/install/>. 3. NGC API key for nvcr.io/ pulls. Get from <https://ngc.nvidia.com/>. If the selected model declares runtimerequirements.gpuhost, append the corresponding --min-driver-version, --min-cuda-version, and --min-container-toolkit-version values to both the check and any approved install command. Do not apply one model's override to unrelated workflows. NGC authentication Persists in ~/.docker/config.json across reboots. Re-run on unauthorized errors. Execution — the four verbs Run a spec-bundle by implementing exactly these four verbs, mutating only the job-record. Status values are the fixed vocabulary from tao-artifacts (PENDING RUNNING COMPLETE ERROR CANCELED UNKNOWN); native docker states map below, with the raw state carried in the transition message. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/tao-run-on-docker