New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Building Classification Models

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

Build and evaluate classification models for supervised learning tasks with labeled data.

MITAuto-check passedData & Analytics

Install Building Classification Models

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill building-classification-models -a claude-code

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace building-classification-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/building-classification-models .claude/skills/building-classification-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
building-classification-models
GitHub stars
2.8k
Token cost
~963 tokens
SKILL.md length
439 words
Files
5 (incl. scripts, references, assets)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Build and evaluate classification models for supervised learning tasks with labeled data.

  • Works in 3 steps: Context Analysis: Claude analyzes the… → Model Generation: The skill utilizes the… → Evaluation and Reporting: The generated…
  • Requesting build a classifier
  • SKILL.md covers Overview, How It Works, When to Use This Skill and Examples, plus 7 more sections
  • Create classification model

What it does

Building Classification Models is an agent skill from jeremylongshore/tons-of-skills-marketplace. Build and evaluate classification models for supervised learning tasks with labeled data. Use when requesting "build a classifier", "create classification model", or "train classifier". Trigger with relevant phrases based on skill purpose.

Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts, reference files and assets (for example `assets/README.md`, `assets/model_config_template.json` 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

  • Requesting build a classifier
  • Create classification model
  • Train classifier
  • With relevant phrases based on skill purpose

Example prompts

  • “build a classifier”
  • “create classification model”
  • “train classifier”
  • “/building-classification-models”

Requirements

  • Python 3
  • 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. Context Analysis: Claude analyzes the user's request, identifying the dataset, target variable, and any specific requirements for the…
  2. Model Generation: The skill utilizes the classification-model-builder plugin to generate code for training a classification model based on…
  3. Evaluation and Reporting: The generated model is trained and evaluated using appropriate metrics (e.g., accuracy, precision, recall…

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

Building Classification Models loads about 963 tokens when it runs, and up to ~981 if it reads all its reference files. Until then it costs about 68 tokens; SKILL.md has 439 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~963
With references · SKILL.md plus every file in references/, read only if the agent opens them
~981

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). 439 words, ~963 tokens.

Download SKILL.mdSave it as .claude/skills/building-classification-models/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
building-classification-models
description
Build and evaluate classification models for supervised learning tasks with labeled data. Use when requesting "build a classifier", "create classification model", or "train classifier". Trigger with relevant phrases based on skill purpose.
allowed-tools
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
compatibility
Designed for Claude Code
version
1.22.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
ai, classification-models

Classification Model Builder

Build and evaluate classification models for supervised learning tasks with labeled data.

Overview

This skill empowers Claude to efficiently build and deploy classification models. It automates the process of model selection, training, and evaluation, providing users with a robust and reliable classification solution. The skill also provides insights into model performance and suggests potential improvements.

How It Works

  1. Context Analysis: Claude analyzes the user's request, identifying the dataset, target variable, and any specific requirements for the classification model.
  2. Model Generation: The skill utilizes the classification-model-builder plugin to generate code for training a classification model based on the identified dataset and requirements. This includes data preprocessing, feature selection, model selection, and hyperparameter tuning.
  3. Evaluation and Reporting: The generated model is trained and evaluated using appropriate metrics (e.g., accuracy, precision, recall, F1-score). Performance metrics and insights are then provided to the user.

When to Use This Skill

This skill activates when you need to:

  • Build a classification model from a given dataset.
  • Train a classifier to predict categorical outcomes.
  • Evaluate the performance of a classification model.

Examples

Example 1: Building a Spam Classifier

User request: "Build a classifier to detect spam emails using this dataset."

The skill will:

  1. Analyze the provided email dataset to identify features and the target variable (spam/not spam).
  2. Generate Python code using the classification-model-builder plugin to train a spam classification model, including data cleaning, feature extraction, and model selection.
Show full SKILL.md (200 more words)Show less
Example 2: Predicting Customer Churn

User request: "Create a classification model to predict customer churn using customer data."

The skill will:

  1. Analyze the customer data to identify relevant features and the churn status.
  2. Generate code to build a classification model for churn prediction, including data validation, model training, and performance reporting.

Best Practices

  • Data Quality: Ensure the input data is clean and preprocessed before training the model.
  • Model Selection: Choose the appropriate classification algorithm based on the characteristics of the data and the specific requirements of the task.
  • Hyperparameter Tuning: Optimize the model's hyperparameters to achieve the best possible performance.

Integration

This skill integrates with the classification-model-builder plugin to automate the model building process. It can also be used in conjunction with other plugins for data analysis and visualization.

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 4 other files (scripts, references, assets) in skills/.curated/building-classification-models of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • assets/README.md
  • assets/model_config_template.json
  • references/README.md
  • scripts/README.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Building Classification 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.

Building Classification Models compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Building Classification Models this skilljeremylongshore/tons-of-skills-marketplace2.8k—~963Automated safety check: PassMIT
Scikit LearnzLanqing/codex-claude-academic-skills4.7k16 repos~3.9kAutomated safety check: PassBSD-3-Clause
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

Similar skills

  • Scikit Learn

    zLanqing/codex-claude-academic-skills

    Machine learning in Python with scikit-learn. An agent skill from zLanqing/codex-claude-academic-skills.

    4.7k GitHub starsUsed in 16 repos~3.9k tokens
    Data & AnalyticsAuto-check passed

  • Agentic Kaggle Workflow

    FrankS-IntelLab/agentic-kaggle-skill

    Takes a Kaggle competition from rules and validation design through baselines, ensembling and notebook architecture to a scored submission.

    188 GitHub stars~4k tokensUpdated 3 mo ago
    Data & AnalyticsAuto-check passed

  • Senior Data Scientist

    Raidriar7170/hermes-skilleval

    World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics.

    125 GitHub starsUsed in 5 repos~1.4k tokens
    Data & AnalyticsAuto-check passed

  • Geoml

    italo-goncalves/geoML

    Working knowledge of the geoML Python package (github.com/italo-goncalves/geoML): variational Gaussian processes for spatial data, implicit geological modelling, block models, drillhole data…

    109 GitHub stars~4.9k tokensUpdated today
    Data & AnalyticsAuto-check passed

  • QuantMind Training Config Generator

    qusong0627/QuantMind

    Turns a plain-language model training request into a validated QuantMind training config file that can be imported from the Model Training page.

    1.7k GitHub stars~1.5k tokensUpdated today
    Data & AnalyticsAuto-check passed

  • Retention Analysis

    liangdabiao/claude-data-analysis-ultra-main

    Analyze user retention and churn using survival analysis, cohort analysis, and machine learning.

    290 GitHub stars~1.3k tokensUpdated 5 mo ago
    Data & AnalyticsAuto-check: notes

More from jeremylongshore/tons-of-skills-marketplace

All 3,342 skills in this repo

  • Performing Security Code Review

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill enables AI assistant to conduct a security-focused code review using the security-agent plugin.

    2.8k GitHub starsUsed in 2 repos~1.3k tokens
    Auto-check: notes

  • Adapting Transfer Learning Models

    jeremylongshore/tons-of-skills-marketplace

    Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques.

    2.8k GitHub stars~1.1k tokensUpdated today
    Auto-check passed

  • Agent Context Loader

    jeremylongshore/tons-of-skills-marketplace

    Execute proactive auto-loading: automatically detects and loads agents.md files.

    2.8k GitHub stars~1.1k tokensUpdated today
    Auto-check passed

  • Aggregating Performance Metrics

    jeremylongshore/tons-of-skills-marketplace

    Aggregate and centralize performance metrics from applications, systems, databases, caches, and services.

    2.8k GitHub stars~1.2k tokensUpdated today
    Auto-check passed

  • Analyzing Capacity Planning

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill enables AI assistant to analyze capacity requirements and plan for future growth.

    2.8k GitHub stars~947 tokensUpdated today
    Auto-check passed

  • Analyzing Database Indexes

    jeremylongshore/tons-of-skills-marketplace

    Process use when you need to work with database indexing. An agent skill from jeremylongshore/tons-of-skills-marketplace.

    2.8k GitHub stars~2k tokensUpdated today
    Auto-check passed

Categories

Questions about Building Classification Models

What does Building Classification Models do?

Build and evaluate classification models for supervised learning tasks with labeled data. Building Classification Models is an agent skill from jeremylongshore/tons-of-skills-marketplace. Build and evaluate classification models for supervised learning tasks with labeled data.

When should I use Building Classification Models?

Building Classification Models fits situations like: requesting build a classifier; create classification model; train classifier; with relevant phrases based on skill purpose.

How do I install Building Classification Models in Claude Code?

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

How do I install Building Classification Models in Codex?

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

Can I use Building Classification 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 building-classification-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/building-classification-models, .gemini/skills/building-classification-models, .github/skills/building-classification-models and .opencode/skills/building-classification-models in your project.

What does Building Classification Models need to run?

SKILL.md names no scripts, command-line tools or credentials: Building Classification Models is instructions for the agent only. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(cmd:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Building Classification 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 Building Classification 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 Building Classification Models use?

Building Classification 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 Building Classification Models use?

About 963 tokens (SKILL.md is roughly 3.9k 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 18 tokens, read only when the agent opens those files.

What are the alternatives to Building Classification Models?

Skills that share tags, products or a category with Building Classification 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 Building Classification 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.