ml-training

v0.1.0

Machine-learning training and benchmarking on rented cloud GPUs: prebaked RunPod images that boot in seconds instead of minutes, pod lifecycle scripts, GPU selection and pricing ladders, and the provisioning pitfall catalog

CodexClaude Code1 Skill

By Seyed Yahya ShiraziLicense: BSD-3-Clause46 GitHub starsUpdated 3 days ago

Directory evidence

Runtimes: Codex and Claude Code
Parsed components: 1 skill or MCP entry
Source updated: Sep 21, 2026
Manifest status: Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install ml-training for Codex and Claude Code

Installs for the current user

codex plugin marketplace add neuromechanist/research-skills
codex plugin marketplace upgrade research-skills
codex plugin add ml-training@research-skills

Paste and run these commands in a terminal with Codex. They add and refresh the research-skills catalog, then install this plugin.

Compatibility: the page URL and API slug “ml-training” remain stable.

Codex: ml-training@agent-plugin-marketplace → ml-training@research-skills

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually

$ git clone https://github.com/neuromechanist/research-skills

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is plugins/ml-training/.

Plugin files

plugins/ml-training/

├── .codex-plugin/plugin.json
├── .claude-plugin/plugin.json
└── skills/runpod/SKILL.md

Included Skills1

runpodskills/runpod/SKILL.md

This skill should be used when the user says "spin up a RunPod pod", "rent a GPU", "run this on a cloud GPU", "RunPod", "prebake a GPU image", "my pod takes 10 minutes to install", "boot-to-ready", "which GPU should I rent", "2x A100 or 1x H100", "is Modal cheaper", "multi-GPU pod", "fan out this grid across pods", "run the benchmark in parallel", "pod fleet", "only one pod launched", "pod ssh permission denied", "ssh exit 255", "GLIBC not found on my pod", "terminate the pod", "how much did that pod cost", or wants to provision, script, fan out, debug, or cost-control ephemeral cloud GPU pods for training, benchmarking, or serving.

Plugin manifests2

plugins/ml-training/.codex-plugin/plugin.json

{
  "name": "ml-training",
  "version": "0.1.0",
  "description": "Machine-learning training and benchmarking on rented cloud GPUs: prebaked RunPod images that boot in seconds instead of minutes, pod lifecycle scripts, GPU selection and pricing ladders, and the provisioning pitfall catalog",
  "author": {
    "name": "Seyed Yahya Shirazi",
    "email": "[email protected]"
  },
  "license": "BSD-3-Clause",
  "skills": "./skills/",
  "keywords": [
    "runpod",
    "gpu",
    "cloud-gpu",
    "cuda",
    "docker",
    "provisioning",
    "training",
    "benchmarking",
    "inference",
    "cost-control",
    "ssh"
  ]
}

plugins/ml-training/.claude-plugin/plugin.json

{
  "name": "ml-training",
  "version": "0.1.0",
  "description": "Machine-learning training and benchmarking on rented cloud GPUs: prebaked RunPod images that boot in seconds instead of minutes, pod lifecycle scripts, GPU selection and pricing ladders, and the provisioning pitfall catalog",
  "author": {
    "name": "Seyed Yahya Shirazi",
    "email": "[email protected]"
  },
  "license": "BSD-3-Clause",
  "skills": "./skills/",
  "keywords": [
    "runpod",
    "gpu",
    "cloud-gpu",
    "cuda",
    "docker",
    "provisioning",
    "training",
    "benchmarking",
    "inference",
    "cost-control",
    "ssh"
  ]
}

For maintainers

If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.

[ml-training on Agent Plugins Marketplace](https://pluginsmp.com/plugins/ml-training)