tao-run-on-slurm SKILL.md skillA
tao-run-on-slurm from fastfold-ai/sandwalk is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add fastfold-ai/sandwalk/tao-run-on-slurm@v0.1.1Pins v0.1.1 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- fastfold-ai/sandwalk
- Path
cli/src/skills/tao_run_on_slurm/SKILL.md- Versions recorded
- 1
- Latest version
- v0.1.1, committed Oct 21, 2026
- Size
- 3,761 bytes
- Repository stars
- 23
- License
- Apache-2.0
Remote SLURM GPU cluster execution over SSH with sbatch/srun, Pyxis/Enroot containers, and Lustre-backed results. Use when running GPU training, evaluation, or inference jobs on an on-prem or DGX SLURM cluster.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# NVIDIA `tao-run-on-slurm` — SLURM GPU Cluster Execution over SSH Remote GPU compute skill for clusters managed by **SLURM** (`https://github.com/NVIDIA/skills/tree/HEAD/skills/tao-run-on-slurm`). Jobs are staged from your local machine to a login node over SSH, submitted with `sbatch`, and monitored via `squeue` / `sacct` / `scancel` (with optional Pyxis/Enroot `.sqsh` container execution). ## 1. Preflight + SSH 1. Confirm passwordless SSH (`ssh -o BatchMode=yes`) to the SLURM login host works (or configure the host in **Dashboard → SSH & Clusters**). 2. The launch machine only needs `ssh` (and `ssh.exec` / `ssh.slurm_status` / `ssh.sync`); `sbatch`, `srun`, `squeue`, `sacct`, and shared storage (`/scratch` or Lustre) live on the remote SLURM cluster. 3. For private `nvcr.io` images with Pyxis/Enroot, install `~/.config/enroot/.credentials` on the cluster via a mode-600 stdin pipe rather than inline environment variables. ## 2. The Four Core Verbs (`submit`, `status`, `logs`, `cancel`) ### `submit` 1. **Stage inputs and scripts to the shared cluster workspace** (`ssh.sync` or `rsync -az` to `/scratch/$USER/<job_dir>`). …
Read the whole file at its exact version.
How to install
mdr add fastfold-ai/sandwalk/tao-run-on-slurm@sha256:a050f5fa0dbdd700The line at the top of this page pins the label v0.1.1, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_wilqd2bhs3pj5sr3)
6 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Oct 21, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (3761 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
fastfold-ai/sandwalk · 23 stars · license Apache-2.0 · pushed 2026-10-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_wilqd2bhs3pj5sr3 GET https://markdownregistry.com/api/v1/resolve?ref=fastfold-ai/sandwalk/tao-run-on-slurm GET https://markdownregistry.com/api/v1/blob/a050f5fa0dbdd700a7d4d388c6eee049bb201c5be4f31471b250e9f895d2936c
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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