Agent skill · software engineering · nvidia
tao-launch-workflow
The mandatory pre-launch gate and four-verb execution contract for every TAO workflow or action. Invoke BEFORE launching anything side-effecting — AutoML, train, evaluate, inference, export, TensorRT engine generation, or DEFT/application workflows — on any execution platform. Covers platform selection, credentials, image confirmation, dataset intake, preflight, the launch review, job records, monitoring, and failure/retry classification. Trigger phrases include "train this model", "run AutoML", "launch on SLURM/docker/k8s/brev/virtualenv", "evaluate my checkpoint", "start a TAO job".
Why this skill is useful
Adds executable scripts for TAO workflow management and preflight checks that are not available in public documentation.
What it needs
Requires bash installed locally. About 11k tokens when loaded. Last updated 2026-08-07. 2,816 stars on the source repository.
What this skill does
TAO Workflow Launch Intake 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). Use this skill before launching any TAO workflow or model action. For direct invocation, run the complete-checkout check in references/platform-preflight.md before Step 0 or any helper. Individual skill installs lack shared scripts; stop if the check fails. Use its verified TAOSKILLBANKPATH for every helper. Step 0 — Execution Mode: Card Packs (check first) Before running a multi-stage application workflow inside this conversation, check whether a compiled card pack ships next to the application skill: Pack exists → prefer the token-efficient path: the pack's driver.sh runs the workflow as fresh per-stage sessions (measured 74-91% cheaper than in-conversation execution, and the only mode validated on small models). Read the pack's README.md for required env, complete THIS gate's items 1-9 for the launch review, then start the pack driver detached instead of executing stages in this conversation. Monitor via the driver log and the run dir's progress marks. No pack → execute normally through this gate. If the workflow will be run repeatedly, suggest compiling a pack once with a strong model — see skills/core/tao-token-efficient-execution (authoring prompt + contracts). The card path replaces only in-conversation stage execution; it never skips this gate. A pack driver launch is side-effecting work and requires the same confirmed launch review. Quick Start Run the platform helper, ask for platform and monitoring preferences, then run the selected platform detail helper before asking for credentials. Non-Negotiable Launch Gate This gate is model-agnostic. Apply it to every TAO model, data action, and application workflow before launching side-effecting work. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/tao-launch-workflow