ai-model-team

Generate trading signals for OKX crypto and US stocks using a multi-model ensemble.

Updated Apr 14, 2026
One-click install
npx skills add https://github.com/erongcao/ai-model-team --skill ai-model-team
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ai-model-team
Source: https://github.com/erongcao/ai-model-team/tree/main
Command: npx skills add https://github.com/erongcao/ai-model-team --skill ai-model-team

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, requests, torch, transformers, vaderSentiment, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive multi-model prediction system for OKX crypto and US stocks, eliminating the need for manual analysis and enhancing trading efficiency.

Core Features & Use Cases

  • Multi-model Analysis: Integrates Kronos, Chronos-2, TimesFM, and VADER FinBERT for a comprehensive view of market trends and sentiment.
  • Data Sources: Utilizes OKX API for crypto and Yahoo Finance for US stocks, ensuring access to real-time and reliable data.
  • Usage Examples: Use the skill to analyze BTC-USDT-SWAP using all models and social sentiment. Obtain a unified signal and confidence level for your trading decisions.

Quick Start

Use the ai-model-team skill to analyze the market for BTC-USDT-SWAP using all models and social sentiment.

Frequently Asked Questions about ai-model-team

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate trading signals for crypto and US stocks using multiple machine learning models?

To generate trading signals for crypto and US stocks, you can use a multi-model ensemble approach that integrates time series forecasting and sentiment analysis. This system utilizes the OKX and Yahoo Finance APIs to produce a unified signal with a confidence level.

What is a multi-model ensemble approach for stock and crypto market prediction?

A multi-model ensemble approach for market prediction combines outputs from several models, such as Kronos, Chronos-2, TimesFM, and VADER FinBERT. This integration provides a comprehensive view of market trends and social sentiment to enhance trading efficiency.

Do I need API access for OKX and Yahoo Finance to run crypto and stock predictions?

Yes, you need API access for OKX and Yahoo Finance to run crypto and stock predictions. The system requires these data sources to fetch real-time market data for processing through its time series forecasting and sentiment analysis models.

Can I use Python and PyTorch for time series forecasting in crypto trading?

Yes, you can use Python and PyTorch for time series forecasting in crypto trading. This solution leverages libraries like torch, transformers, pandas, and numpy to process historical data and generate actionable trading signals.

How does VADER FinBERT sentiment analysis integrate with time series forecasting for trading?

VADER FinBERT sentiment analysis integrates with time series forecasting by combining social sentiment data with price trends. This multi-model approach processes market data and sentiment together to output a unified trading signal and confidence level.

What are the limitations of using machine learning for crypto and stock trading predictions?

Limitations of machine learning for trading predictions include dependence on external API data availability from OKX and Yahoo Finance. The system provides signals and confidence levels but requires users to manage execution risk and market volatility.