Train
Train a machine learning model with specified parameters
- Type
- Slash Command
- Repository
- jeremylongshore/tons-of-skills-marketplace
- GitHub stars
- 2.8k
- License
- MIT
- Repo last updated
- Sep 27, 2026
- Source file
- plugins/ai-ml/ml-model-trainer/commands/train.md
What Train is
Train is a slash command 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 slash command is a reusable prompt saved as a markdown file and run by typing its name after a slash. In Claude Code, custom commands have been merged into skills: a file in .claude/commands/ and a skill folder in .claude/skills/ both create the same kind of command, and existing command files keep working.
Train gives you a repeatable way to run the same instructions without retyping them, optionally with arguments.
How to install Train
Claude Code
- Download train.md from the repository.
- Save it to ~/.claude/commands/ (all projects) or .claude/commands/ (one project). As a skill, you can instead save it as ~/.claude/skills/<name>/SKILL.md.
- Run it by typing / followed by its name.
Claude Cowork
- Turn the command into a skill: create a folder with the file saved as SKILL.md and zip it.
- In Customize → Skills, click +, then upload the ZIP.
- Run it from any task with / and the skill name.
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/commands/train.md, shared under the repository's MIT license. Read the full file on GitHub.
You are an ML training specialist. When this command is invoked:
- Analyze the dataset and target variable
- Select appropriate model type (classification, regression, etc.)
- Configure training parameters
- Train the model with cross-validation
- Generate performance metrics
- Save trained model artifact
Provide code for:
- Data loading and validation
- Model selection and initialization
- Training loop with monitoring
- Evaluation metrics
- Model persistence
Support common frameworks: scikit-learn, PyTorch, TensorFlow, XGBoost.
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 Train?
Train is a slash command for Claude Code and Claude Cowork from the jeremylongshore/tons-of-skills-marketplace repository on GitHub. Train a machine learning model with specified parameters
How do I install Train in Claude Code?
Download train.md from the repository. Save it to ~/.claude/commands/ (all projects) or .claude/commands/ (one project). As a skill, you can instead save it as ~/.claude/skills/<name>/SKILL.md. Run it by typing / followed by its name.
Can I use Train in Claude Cowork?
Turn the command into a skill: create a folder with the file saved as SKILL.md and zip it. In Customize → Skills, click +, then upload the ZIP. Run it from any task with / and the skill name.
Is Train 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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