github-hot-hub

🥈Silver

Tracks GitHub trending repositories since 2021, updating hourly and archiving daily. Useful for developers and operations teams monitoring open-source trends. Integrates with Python workflows and connects to GitHub's API.

7790Updated 1mo ago

Intermediate30min to implementautomation

Saves ~60 min per use

Quick InstallView Source

git clone https://github.com/SnailDev/github-hot-hub.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/SnailDev/github-hot-hub

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Find and record the top 10 trending GitHub repositories in [INDUSTRY] over the past [TIME_PERIOD] hours. Archive the results by day and provide a summary of the most popular repositories, including their names, descriptions, and star counts.

Example Output

# Top 10 Trending GitHub Repositories in AI Development (Last 24 Hours)

## Summary

The following repositories have seen significant activity and engagement in the AI development community over the past 24 hours:

1. **Repository Name**: AI-Model-Training
   - **Description**: A comprehensive library for training and deploying AI models.
   - **Stars**: 1,250
   - **Key Features**: Supports multiple frameworks, easy deployment, and extensive documentation.

2. **Repository Name**: Data-Science-Tools
   - **Description**: A collection of tools for data scientists to streamline their workflows.
   - **Stars**: 980
   - **Key Features**: Includes data cleaning, visualization, and analysis tools.

3. **Repository Name**: Machine-Learning-Workflows
   - **Description**: A set of workflows for machine learning projects.
   - **Stars**: 850
   - **Key Features**: Predefined workflows for common tasks, customizable templates.

4. **Repository Name**: AI-Research-Papers
   - **Description**: A curated list of the latest AI research papers.
   - **Stars**: 720
   - **Key Features**: Regularly updated, categorized by topic, and includes summaries.

5. **Repository Name**: Deep-Learning-Tutorials
   - **Description**: Tutorials and examples for deep learning projects.
   - **Stars**: 650
   - **Key Features**: Step-by-step guides, code examples, and project ideas.

6. **Repository Name**: NLP-Tools
   - **Description**: Tools for natural language processing tasks.
   - **Stars**: 580
   - **Key Features**: Text preprocessing, sentiment analysis, and language translation.

7. **Repository Name**: AI-Ethics
   - **Description**: Resources and discussions on AI ethics.
   - **Stars**: 500
   - **Key Features**: Articles, guidelines, and case studies.

8. **Repository Name**: AI-Model-Zoo
   - **Description**: A collection of pre-trained AI models.
   - **Stars**: 450
   - **Key Features**: Models for various tasks, easy integration, and documentation.

9. **Repository Name**: AI-Project-Templates
   - **Description**: Templates for starting AI projects.
   - **Stars**: 400
   - **Key Features**: Project structures, sample code, and best practices.

10. **Repository Name**: AI-News
   - **Description**: A news aggregator for AI-related news.
   - **Stars**: 350
   - **Key Features**: Daily updates, categorized news, and summaries.

## Detailed Analysis

The top trending repositories reflect the current interests and needs of the AI development community. AI-Model-Training and Data-Science-Tools lead the list, indicating a strong focus on practical tools and frameworks. The inclusion of AI-Research-Papers and AI-Ethics highlights the community's interest in staying updated with the latest research and ethical considerations.

The variety of repositories also shows the diverse needs of AI developers, from practical tools and tutorials to ethical guidelines and news aggregators. This diversity ensures that developers have access to a wide range of resources to support their projects and stay informed about the latest developments in the field.