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.
npx skills add NVIDIA-TAO/tao-skill-bank --skill tao-run-on-slurmgit clone --depth 1 https://github.com/NVIDIA-TAO/tao-skill-bankWrote 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.
[](https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/tao-run-on-slurm)<a href="https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/tao-run-on-slurm"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-run-on-slurm/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.
<a href="https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/tao-run-on-slurm"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-run-on-slurm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
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 Rogue Agent · line 79 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00094 | $0.05119 |
| Opus 5 | $0.00047 | $0.02559 |
| Sonnet 5 | $0.00019 | $0.01024 |
| Haiku 4.5 | $0.00009 | $0.00512 |
Grade A, and why
tao-run-on-slurm 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SLURM
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).
Remote GPU compute platform for clusters managed by SLURM. Jobs are submitted
from the launch host to a login node over SSH, staged on a shared
filesystem, submitted with sbatch, and executed with srun container support.
When to use
Use SLURM when the user has access to a managed GPU cluster, shared Lustre storage, and scheduler-owned GPU allocation. Do not use SLURM for local files that exist only on the agent machine; data and outputs must be reachable from the cluster.
Preflight + SSH
Confirm SLURM_USER and SLURM_HOSTNAME are exported and passwordless SSH to a
login host works (ssh -o BatchMode=yes).
The launch host needs ssh, not local sbatch, srun, Enroot, or a Lustre
mount. Preflight those scheduler, Pyxis, Enroot, and shared-storage dependencies
on the selected remote login/compute frame. Model-specific inspectors may be
streamed from the installed skill over SSH stdin; do not stage an ad-hoc source
patch or treat the launch host as the SLURM frame.
For private nvcr.io images, install ~/.config/enroot/.credentials on the
cluster once per (cluster, user): Pyxis/Enroot does not read NGC_KEY from the
job env, and without persistent credentials, auth-gated pulls fail with "Could
not process JSON input" at job startup. Install it via the printf | ssh
heredoc so the NGC_KEY value never lands in shell history, intermediate files,
or chat output; never cat/echo the value.
If a preflight check fails, the agent prompts the user to authorize the install/fix via Bash. Pip-installable Python requirements are the exception: install them automatically, then rerun preflight.
See references/slurm-ssh-credentials.md for the full preflight script, the
enroot-credentials heredoc, prerequisite key setup (keypair, ssh-copy-id,
known_hosts, container key mounts, 2FA handling), and the SSH failure
remediation prompt.
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- BENCHMARK.md 3.9 KB
- evals/evals.json 759 B
- references/cosmos-slurm-guardrails.md 3.3 KB
- references/detailed-guide.md 704 B
- references/skill_info.yaml 1.3 KB
- references/slurm-container-execution.md 12 KB
- references/slurm-preflight-storage.md 11 KB
- references/slurm-ssh-credentials.md 9.5 KB
- skill-card.md 3.8 KB
- skill.oms.sig 5.9 KB
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.
- 8d ago First seen · 391 lines · 94 tokens per session scan A 8193806ce87b
tao-run-on-slurm is a skill published in the GitHub repository NVIDIA-TAO/tao-skill-bank (88 stars, last pushed today), licensed Apache-2.0. It adds 94 tokens to every session and 5,119 once invoked, about $0.0005 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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