zenithbaseshadow

zenithbaseshadow / r18-anthropics-claude-code-datascience

Public

🤖 Data Science & AI/ML skill suite derived from anthropics/claude-code.

26
0
69% credibility
Found May 02, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

This project adapts an AI coding tool into a suite of 10 commands and 5 workflows for data science and machine learning tasks, featuring structured visual progress and prioritized recommendations.

How It Works

1
🔍 Discover the toolkit

You stumble upon this handy collection of data science tools powered by your favorite AI assistant while searching for ways to make analyzing data easier.

2
📥 Bring it home

You simply copy the toolkit into your AI assistant's special folder so it's ready to use.

3
💬 Chat with your AI

You open a conversation with your AI helper and tell it about the new toolkit to activate it.

4
📊 Dive into data magic

You ask it to profile your data or start a full machine learning project, and it instantly shows clear insights, charts, and step-by-step progress.

5
🔄 Follow the guided path

Whether checking data quality, building models, or setting up reports, you get prioritized suggestions and watch everything unfold smoothly.

6
Choose your adventure
⚡
Quick fix

Handle one data issue fast with instant reports and fixes.

🛤️
Full journey

Tackle end-to-end projects with guided multi-step help.

7
✅ Review and act

You see beautiful summaries, issue lists sorted by importance, and ready-to-do checklists that make decisions easy.

🎉 Data dreams achieved

Your data science work is done faster with smart insights, clean pipelines, and professional results—ready to impress!

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Star Growth

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AI-Generated Review

What is r18-anthropics-claude-code-datascience?

This repo adapts Anthropic's Claude Code CLI into a skill suite for data science and AI/ML tasks, delivering 10 specialized commands like /data-profiling for automated EDA reports and /model-evaluate for performance dashboards, plus 5 multi-step workflows such as ml-project-init for end-to-end ML projects. It tackles the grind of data pipelines, model training, MLOps, and reporting by providing structured CLI interactions with progress panels, findings tables, and action checklists right in your terminal. Install via bash clone into Claude's skills directory, no specific language lock-in beyond Claude's ecosystem.

Why is it gaining traction?

It stands out by layering DS-specific commands on Claude's official code tools, with consistent UI like real-time progress bars and severity-sorted issue tables that cut through analysis chaos. Developers hook on the workflows for repeatable processes like model retraining or data migration, saving hours on boilerplate while integrating seamlessly with github data storage and github data tables. The prioritized action plans with time estimates make it a practical boost over generic AI/ML notebooks.

Who should use this?

Data scientists in data science jobs or data science master programs handling EDA, feature engineering, and anomaly detection. ML engineers building pipelines or A/B tests, especially those in data science studium, data science weiterbildung, or data science und künstliche intelligenz tracks. Analytics teams optimizing SQL queries or generating data contracts for github data residency compliance.

Verdict

With 11 stars and a 0.7% credibility score, it's an early, README-only fork lacking tests or broad adoption, but promising for Anthropic Claude users in AI/ML. Grab it if you're prototyping data science projects; skip for production without forking and hardening.

(178 words)

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