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Agent skill

Training Machine Learning Models

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Build train machine learning models with automated workflows.

MITAuto-check passedData & Analytics

Install Training Machine Learning Models

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill training-machine-learning-models -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace training-machine-learning-models --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/training-machine-learning-models .claude/skills/training-machine-learning-models && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
training-machine-learning-models
GitHub stars
2.8k
Token cost
~1k tokens
SKILL.md length
468 words
Files
7 (incl. scripts, references, assets)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Build train machine learning models with automated workflows.

  • Works in 3 steps: Data Analysis and Preparation: The skill… → Model Selection and Training: Based on… → Performance Evaluation and Persistence:…
  • Asked to train model
  • SKILL.md covers Overview, How It Works, When to Use This Skill and Examples, plus 7 more sections
  • With relevant phrases based on skill purpose

What it does

Training Machine Learning Models is an agent skill from jeremylongshore/tons-of-skills-marketplace. Build train machine learning models with automated workflows. Analyzes datasets, selects model types (classification, regression), configures parameters, trains with cross-validation, and saves model artifacts. Use when asked to "train model" or "evalua... Trigger with relevant phrases based on skill purpose.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts, reference files and assets (for example `assets/README.md`, `assets/evaluation_report_template.md` and `references/README.md`). Compatibility notes: Designed for Claude Code

It sits in Data & Analytics, covering Machine learning. 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. The licence is MIT.

When your agent uses it

  • Asked to train model
  • With relevant phrases based on skill purpose

Example prompts

  • “train model”
  • “/training-machine-learning-models”

Requirements

  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Glob, Bash(cmd:*)

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Data Analysis and Preparation: The skill analyzes the provided dataset and identifies the target variable, determining the appropriate…
  2. Model Selection and Training: Based on the data analysis, the skill selects a suitable machine learning model and configures the training…
  3. Performance Evaluation and Persistence: After training, the skill generates performance metrics to evaluate the model's effectiveness…

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Grep
    • Glob
    • Bash(cmd:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Training Machine Learning Models loads about 1k tokens when it runs, and up to ~1k if it reads all its reference files. Until then it costs about 86 tokens; SKILL.md has 468 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~86
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 468 words, ~1,019 tokens.

Download SKILL.mdSave it as .claude/skills/training-machine-learning-models/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
training-machine-learning-models
description
Build train machine learning models with automated workflows. Analyzes datasets, selects model types (classification, regression), configures parameters, trains with cross-validation, and saves model artifacts. Use when asked to "train model" or "evalua... Trigger with relevant phrases based on skill purpose.
allowed-tools
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
compatibility
Designed for Claude Code
version
1.23.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
ai, ml, workflow

Ml Model Trainer

Train machine learning models with configurable architectures, loss functions, and optimization strategies across classification, regression, and other task types.

Overview

This skill empowers Claude to automatically train and evaluate machine learning models. It streamlines the model development process by handling data analysis, model selection, training, and evaluation, ultimately providing a persisted model artifact.

How It Works

  1. Data Analysis and Preparation: The skill analyzes the provided dataset and identifies the target variable, determining the appropriate model type (classification, regression, etc.).
  2. Model Selection and Training: Based on the data analysis, the skill selects a suitable machine learning model and configures the training parameters. It then trains the model using cross-validation techniques.
  3. Performance Evaluation and Persistence: After training, the skill generates performance metrics to evaluate the model's effectiveness. Finally, it saves the trained model artifact for future use.

When to Use This Skill

This skill activates when you need to:

  • Train a machine learning model on a given dataset.
  • Evaluate the performance of a machine learning model.
  • Automate the machine learning model training process.

Examples

Example 1: Training a Classification Model

User request: "Train a classification model on this dataset of customer churn data."

The skill will:

  1. Analyze the customer churn data, identify the churn status as the target variable, and determine that a classification model is appropriate.
  2. Select a suitable classification algorithm (e.g., Logistic Regression, Random Forest), train the model using cross-validation, and generate performance metrics such as accuracy, precision, and recall.
Show full SKILL.md (220 more words)Show less
Example 2: Training a Regression Model

User request: "Train a regression model to predict house prices based on features like size, location, and number of bedrooms."

The skill will:

  1. Analyze the house price data, identify the price as the target variable, and determine that a regression model is appropriate.
  2. Select a suitable regression algorithm (e.g., Linear Regression, Support Vector Regression), train the model using cross-validation, and generate performance metrics such as Mean Squared Error (MSE) and R-squared.

Best Practices

  • Data Quality: Ensure the dataset is clean and properly formatted before training the model.
  • Feature Engineering: Consider feature engineering techniques to improve model performance.
  • Hyperparameter Tuning: Experiment with different hyperparameter settings to optimize model performance.

Integration

This skill can be used in conjunction with other data analysis and manipulation tools to prepare data for training. It can also integrate with model deployment tools to deploy the trained model to production.

Prerequisites

  • Appropriate file access permissions
  • Required dependencies installed

Instructions

  1. Invoke this skill when the trigger conditions are met
  2. Provide necessary context and parameters
  3. Review the generated output
  4. Apply modifications as needed

Output

The skill produces structured output relevant to the task.

Error Handling

  • Invalid input: Prompts for correction
  • Missing dependencies: Lists required components
  • Permission errors: Suggests remediation steps

Resources

  • Project documentation
  • Related skills and commands

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references, assets) in skills/.curated/training-machine-learning-models of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • assets/README.md
  • assets/evaluation_report_template.md
  • assets/example_dataset.csv
  • assets/requirements.txt
  • references/README.md
  • scripts/README.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Training Machine Learning Models next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Training Machine Learning Models compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Training Machine Learning Models this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1kAutomated safety check: PassMIT
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Agentic Kaggle WorkflowFrankS-IntelLab/agentic-kaggle-skill188—~4kAutomated safety check: PassMIT
Senior Data ScientistRaidriar7170/hermes-skilleval1255 repos~1.4kAutomated safety check: PassMIT
Geomlitalo-goncalves/geoML109—~4.9kAutomated safety check: PassGPL-3.0
QuantMind Training Config Generatorqusong0627/QuantMind1.7k—~1.5kAutomated safety check: PassAGPL-3.0

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Categories

Questions about Training Machine Learning Models

What does Training Machine Learning Models do?

Build train machine learning models with automated workflows. Training Machine Learning Models is an agent skill from jeremylongshore/tons-of-skills-marketplace. Build train machine learning models with automated workflows.

When should I use Training Machine Learning Models?

Training Machine Learning Models fits situations like: asked to train model; with relevant phrases based on skill purpose.

How do I install Training Machine Learning Models in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill training-machine-learning-models -a claude-code`. Or copy the skill folder (skills/.curated/training-machine-learning-models in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/training-machine-learning-models in your project. Claude Code loads it when a task matches its description.

How do I install Training Machine Learning Models in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill training-machine-learning-models -a codex`. Or copy the skill folder (skills/.curated/training-machine-learning-models in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/training-machine-learning-models in your project. Codex loads it when a task matches its description.

Can I use Training Machine Learning Models in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill training-machine-learning-models -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/training-machine-learning-models, .gemini/skills/training-machine-learning-models, .github/skills/training-machine-learning-models and .opencode/skills/training-machine-learning-models in your project.

What does Training Machine Learning Models need to run?

SKILL.md names no scripts, command-line tools or credentials: Training Machine Learning Models is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(cmd:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Training Machine Learning Models access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Training Machine Learning Models safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Training Machine Learning Models use?

Training Machine Learning Models is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Training Machine Learning Models use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 15 tokens, read only when the agent opens those files.

What are the alternatives to Training Machine Learning Models?

Skills that share tags, products or a category with Training Machine Learning Models: Scikit Learn (zLanqing/codex-claude-academic-skills, 4.7k stars), Agentic Kaggle Workflow (FrankS-IntelLab/agentic-kaggle-skill, 188 stars), Senior Data Scientist (Raidriar7170/hermes-skilleval, 125 stars) and Geoml (italo-goncalves/geoML, 109 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Training Machine Learning Models?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.