✨ What is Omni-X?

Omni-X is a skill project designed specifically for AI agents to extract X (Twitter) data without using the official API. Built on top of the excellent TweeterPy library, it provides a standardized interface for AI agents to dynamically discover and execute X data extraction skills.

πŸ™ Acknowledgments

Special thanks to @iSarabjitDhiman for creating and maintaining TweeterPy, which makes this project possible. All Twitter data extraction capabilities in Omni-X are powered by TweeterPy.

TweeterPy Repository: https://github.com/iSarabjitDhiman/TweeterPy

🎯 Key Features

πŸ€–

AI Agent Ready

Standardized interface designed specifically for AI agents with dynamic skill discovery and execution

πŸ”

Comprehensive Data

Extract tweets, followers, followings, profiles, media, and search results

⚑

Easy Integration

Simple Python interface with consistent response format and error handling

πŸ”“

No API Key

Works without official Twitter API - no rate limits or API costs

πŸ“¦

Structured Responses

All skills return standardized JSON responses with metadata

πŸ”§

Extensible

Easy to add new skills without changing the interface

πŸ› οΈ Available Skills

get_user_profile

Extract user profile information including bio, followers count, and more

get_user_tweets

Extract user's recent tweets with pagination support

get_user_followers

Extract user's followers list with detailed information

get_user_followings

Extract user's following list with detailed information

get_user_media

Extract media content from user's tweets (images, videos)

search_tweets

Search tweets by query with multiple filter options

πŸ’» Quick Start

from scripts import TwitterSkillInterface

# Initialize with auth_token (recommended)
interface = TwitterSkillInterface(auth_token="your_auth_token")

# Discover available skills
skills = interface.get_available_skills()

# Execute a skill
result = interface.execute_skill(
    skill_name="get_user_tweets",
    parameters={"username": "elonmusk", "count": 5}
)

# Process results
if result["success"]:
    print(f"Retrieved {result['count']} tweets")
    for tweet in result["data"]:
        print(tweet)

πŸ” Login Requirements

πŸ“¦ Installation

# Clone the repository
git clone https://github.com/HardBrick21/Omni-X.git
cd Omni-X

# Install dependencies
pip install -r requirements.txt

# Or install as package
pip install -e .

πŸ“š Documentation

πŸ“– README

Project overview and basic usage

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πŸ“‹ SKILL.md

Core skill definition and usage guide

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πŸ€– AI Agent Guide

Complete integration guide for AI agents

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πŸ” Login Guide

Authentication and login instructions

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βš™οΈ Installation Guide

Detailed installation and setup

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Chinese README documentation

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🌟 Why Use Omni-X?

  • Dynamic Discovery: AI agents can query available skills and their parameters at runtime
  • Standardized Execution: All skills use the same execute_skill() method
  • Structured Responses: Consistent response format with success status and metadata
  • Error Handling: Graceful error handling with informative messages
  • No API Costs: Extract Twitter data without official API keys or rate limits
  • Easy Integration: Simple Python interface that works with any AI agent framework

πŸš€ Get Started Now