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Plugin

Ml Model Trainer

Train and optimize machine learning models with automated workflows

Type
Plugin
GitHub stars
2.8k
License
MIT
Repo last updated
Sep 27, 2026
Version
1.23.0
Author
Claude Code Plugins

What Ml Model Trainer is

Ml Model Trainer is a plugin published in the jeremylongshore/tons-of-skills-marketplace repository on GitHub, which has about 2.8k stars. The repository describes itself as: “Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.”

A plugin is a package that bundles skills, slash commands, subagents, hooks, and MCP connectors so they install together. Plugins are plain files with a manifest at .claude-plugin/plugin.json, and they work in both Claude Code and Claude Cowork.

Installing Ml Model Trainer adds everything it ships in one step. Connectors inside a plugin still need to be connected separately, and hooks and subagents only run in Cowork and Claude Code, not in regular chat.

How to install Ml Model Trainer

Claude Code

  1. Add the repository as a plugin marketplace: claude plugin marketplace add jeremylongshore/tons-of-skills-marketplace
  2. Install the plugin: claude plugin install ml-model-trainer@<marketplace-name>, using the marketplace name from the repository's .claude-plugin/marketplace.json.
  3. Restart the session if the new skills or commands don't appear straight away.

Claude Cowork

  1. Open Customize → Plugins and choose Add marketplace.
  2. Enter jeremylongshore/tons-of-skills-marketplace (the owner/repo shorthand works for GitHub).
  3. Find Ml Model Trainer in the list, click Install, then connect any connectors it needs from its Connectors tab.

New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.

Inside the source file

An excerpt from plugins/ai-ml/ml-model-trainer/.claude-plugin/plugin.json, shared under the repository's MIT license. Read the full file on GitHub.

Train and optimize machine learning models with automated workflows.

Installation

/plugin install ml-model-trainer@claude-code-plugins-plus

Usage

/train

Features

  • Automated model training
  • Cross-validation
  • Performance metrics
  • Model persistence
  • Multi-framework support

Requirements

  • Python 3.8+
  • scikit-learn, pandas, numpy

License

MIT

Before you install

  • Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
  • Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
  • Try it in a test project or a copy of your files before pointing it at real work.
  • Pin the version you tested, and review changes before updating.
  • Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.

FAQ

What is Ml Model Trainer?

Ml Model Trainer is a plugin for Claude Code and Claude Cowork from the jeremylongshore/tons-of-skills-marketplace repository on GitHub. Train and optimize machine learning models with automated workflows

How do I install Ml Model Trainer in Claude Code?

Add the repository as a plugin marketplace: claude plugin marketplace add jeremylongshore/tons-of-skills-marketplace Install the plugin: claude plugin install ml-model-trainer@<marketplace-name>, using the marketplace name from the repository's .claude-plugin/marketplace.json. Restart the session if the new skills or commands don't appear straight away.

Can I use Ml Model Trainer in Claude Cowork?

Open Customize → Plugins and choose Add marketplace. Enter jeremylongshore/tons-of-skills-marketplace (the owner/repo shorthand works for GitHub). Find Ml Model Trainer in the list, click Install, then connect any connectors it needs from its Connectors tab.

Is Ml Model Trainer safe to install?

It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.

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Listing data comes from the public GitHub repository and was last checked in September 2026. Excerpts are © their authors and shared under MIT. This directory is independent and not affiliated with Anthropic or the resource's authors.