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 ma-compbio-lab/SkillFoundry --skill gpu-jobs-startergit clone --depth 1 https://github.com/ma-compbio-lab/SkillFoundryWrote 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/ma-compbio-lab/skillfoundry/gpu-jobs-starter)<a href="https://agentmods.dev/skills/ma-compbio-lab/skillfoundry/gpu-jobs-starter"><img src="https://agentmods.dev/badge/skills/ma-compbio-lab/skillfoundry/gpu-jobs-starter/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/ma-compbio-lab/skillfoundry/gpu-jobs-starter"><img src="https://agentmods.dev/badge/skills/ma-compbio-lab/skillfoundry/gpu-jobs-starter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.00140 |
| Opus 5.5 | $0.00000 | $0.00056 |
| Sonnet 5.5 | $0.00000 | $0.00028 |
| Haiku 4.5 | $0.00000 | $0.00014 |
Grade A, and why
gpu-jobs-starter 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 1mo 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.
This is a copy
88% identical to agronomic-experiment-design-starter — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
GPU jobs Starter
Use this starter when a task lands in the GPU jobs frontier leaf and the repository has curated resources but no dedicated runtime implementation yet.
What this starter does
- Summarizes the local resource anchors for the leaf.
- Emits a machine-readable starter plan with promotion steps.
- Gives the agent a stable local entry point before a full runtime skill exists.
How to use it
Run python3 skills/hpc/gpu-jobs-starter/scripts/run_frontier_starter.py --out scratch/frontier/gpu-jobs-starter.json.
Then inspect refs.md and examples/resource_context.json to promote the starter into a concrete executable workflow.
What ships with it
7 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.
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.
- 1mo ago First seen · 17 lines · 0 tokens per session scan A e341c1ef88bf
gpu-jobs-starter is a skill published in the GitHub repository ma-compbio-lab/SkillFoundry (43 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 140 tokens. A static security scan graded it A with 0 findings. It is 88% identical to agronomic-experiment-design-starter, differing in 6 lines, and is treated as a copy.
Other skills, from other repositories
remote-compute-ssh
Evaluate and use SSH Remote Compute before choosing where to run GPU, high-memory, parallel, batch, model-inference, bioinformatics, or other long-running scientific work; supports short remote commands and asynchronous jobs with automatic harvest and analysis.
compute-env-setup
Prepare reproducible setup instructions and validate a user-managed named software environment on an Open-Science SSH Compute Host, including direct SSH and Slurm hosts. Use when a remote job needs packages, modules, cache variables, or a repeatable activation that the host does not already provide.
remote-compute-ssh
Submit recoverable SSH-direct research Runs with live progress cards and model-free monitoring, including Slurm, PBS, LSF, and Grid Engine batch jobs from a cluster login node.
by-deploy-compute
BY is a local-first agent. The default compute provider is "local" (see .by/config.json → compute.defaultprovider). This skill teaches you how to stand up each design and folding tool on hardware the user owns or pays for directly — a personal GPU workstation, a RunPod pod, a Modal app, or a generic SLURM/PBS cluster…
probe-compute-environment
Inspect a registered execution server before compute planning and interpret its persisted capability profile. Use when a server is added, when the user clicks Probe, before enabling an unfamiliar SSH/WSL resource, or when deciding whether GPU, sudo/root, a scheduler, Python, R, conda, mamba, or environment modules are…
remote-compute
Use when the user asks to run, submit, monitor, or cancel a job on a remote machine over SSH — their own GPU/CPU server, a workstation, or a Slurm cluster ("the cluster", a login node, "my 3090 box", "the compute server"). Picks a saved machine, runs the work directly over SSH (or via Slurm when present), tracks it…