ai4science-studio: Skill for Cursor

.cursor/skills/ai4science-run-models/SKILL.md

ai4science-run-models is a skill for Cursor from AMDResearch/ai4science-studio. It costs 38 tokens per session (1,153 once invoked), scanned A, original, MIT.

A set of instructions for launching models in AI4Science Studio, including checking cluster settings, reading model metadata, choosing a container, and selecting a run recipe. A recipe is a prepared set of settings and commands for a particular task.

In plain words
What is it for?
Use it when running, executing, or launching any model in the repository, including checking cluster configuration and model requirements before submission.
Why use it?
It gives the coding agent a consistent process for finding the right model, checking the environment, and starting it with suitable hardware and software settings.

Skill for Cursor

Written for Cursor: installed under .cursor/.

This is AMDResearch/ai4science-studio's own configuration. It tells Cursor how to work on ai4science-studio itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai4science-studio configures →

Reuse

Borrowing it

Nothing to install: this file belongs to AMDResearch/ai4science-studio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/AMDResearch/ai4science-studio/main/.cursor/skills/ai4science-run-models/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/AMDResearch/ai4science-studio

Made for: Cursor.

Wrote 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.

agentmods badge for ai4science-run-models

README.md
[![agentmods](https://agentmods.dev/badge/skills/amdresearch/ai4science-studio/ai4science-run-models/github.svg)](https://agentmods.dev/skills/amdresearch/ai4science-studio/ai4science-run-models)
Your own site
<a href="https://agentmods.dev/skills/amdresearch/ai4science-studio/ai4science-run-models"><img src="https://agentmods.dev/badge/skills/amdresearch/ai4science-studio/ai4science-run-models/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.

agentmods 80×15 button for ai4science-run-models

Your own site · 80×15
<a href="https://agentmods.dev/skills/amdresearch/ai4science-studio/ai4science-run-models"><img src="https://agentmods.dev/badge/skills/amdresearch/ai4science-studio/ai4science-run-models.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,153 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.01153
Opus 5.5 $0.00015 $0.00461
Sonnet 5.5 $0.00008 $0.00231
Haiku 4.5 $0.00004 $0.00115

Measured 1mo ago against content hash fe01281410c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai4science-run-models 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.

.cursor/skills/ai4science-run-models/SKILL.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Running models in AI4Science Studio

Use this skill when a user asks to run, execute, or launch any model in the repository.

Step 0: Check for cluster config

Before anything else, check if a cluster config exists:

# Check both locations
test -f .cluster-config.yaml && echo "repo-local" || \
test -f ~/.config/ai4science-studio/cluster.yaml && echo "user-level" || \
echo "missing"

If missing, tell the user: "No cluster configuration found. Running /init-cluster to detect your cluster environment." Then run the init-cluster flow (auto-discover GPU, SLURM, containers, paths) before proceeding.

If a config exists, read it and use its values as defaults for SLURM partition, account, container runtime, GPU arch, and scratch paths throughout the run. Still confirm with the user if any value is empty or looks stale.

Step 1: Identify the model

  1. Read models.yaml at the repo root to find the model by name, slug, or HF id.
  2. Read <domain>/models/<slug>/model.yaml for full metadata: recipes, env vars, container image, hardware requirements.

Step 2: Determine the task

Match the user's request to a recipe in model.yaml:

  • "run inference" / "predict" / "generate" → look for task: inference
  • "train" / "fine-tune" / "pair-tune" → look for task: train or task: finetune
  • "ensemble" → look for task: ensemble

Step 3: Ask the user for required inputs

Read the env_vars section of model.yaml. For every variable marked required: true that has default: null, ask the user for the value. Present the question with the variable's description.

For common patterns, always offer three options — provide manually, generate/build, or auto-discover:

  • SIF path → "Do you have an Apptainer SIF file? (Yes / No — I'll generate the pull command / Auto-discover — I'll search the filesystem)"
  • Overlay → "Do you have a pre-built overlay? (Yes / No, build one / No, skip overlay / Auto-discover — I'll search for an existing one)"
  • Upstream repo → "Do you have the repo cloned? (Yes / No — I'll generate the clone command / Auto-discover — I'll search the filesystem)"
  • SLURM partition/account → "How should I determine your partition/account? (Provide manually / Auto-discover — I'll query SLURM)"

Read the full file on GitHub · 101 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 1mo ago Changed · -13 lines fe01281410c8
  2. 1mo ago Changed 66ffa316f0aa
  3. 2mo ago First seen · 114 lines · 38 tokens per session scan A 4365d2c38bfc

Subscribe to this mod's changes

ai4science-run-models is a skill published in the GitHub repository AMDResearch/ai4science-studio (4 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 1,153 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.

Related

ai4science-run-models compared with skills from other repositories

ai4science-run-models next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
ai4science-run-modelsAMDResearch/ai4science-studioSkill4yesterdayMITA38Cursor
nextflow-workflow-enginejaechang-hits/SciAgent-SkillsSkill3842d agononeD84Claude Code
figure-styleaipoch/open-scienceSkill5.5ktodayApache-2.0A91Claude Code, Codex
remote-compute-sshaipoch/open-scienceSkill5.5ktodayApache-2.0A53Claude Code, Codex
batch-processing-clinical-textmaziyarpanahi/openmedSkill5.8kyesterdayApache-2.0A161Claude Code
coding-hcc-risk-adjustmentmaziyarpanahi/openmedSkill5.8kyesterdayApache-2.0A200Claude Code
mapping-to-snomedmaziyarpanahi/openmedSkill5.8kyesterdayApache-2.0A205Claude Code