AlphaGBM/skills

Bring realtime market data and research workflows into Claude Code, Cursor & beyond — 29 open-source Skills for stocks, options and commodities.

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AlphaGBM/skills has 3.5k+ stars and 300+ forks on GitHub, is written in Python, and was last pushed on Oct 6, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 13 minutes ago
Added to GitGenius on September 21st, 2026
Created on April 6th, 2026
Open Issues & Pull Requests: 0 (+0)
GitHub issues: Enabled
Number of forks: 332
Total Stargazers: 3,668 (+0)
Total Subscribers: 149 (+0)

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Detailed Description

Skills is a collection of open-source tools that integrate realtime market data and research workflows into Claude Code, Cursor, and other AI coding environments.

The project addresses the challenge of accessing financial market data and performing quantitative analysis within AI-assisted coding platforms. It provides a set of Skills—modular tools that extend the capabilities of Claude Code and Cursor—to fetch and analyze stocks, options, and commodities data. Rather than requiring developers to build custom integrations or switch between applications, Skills brings market research directly into the coding environment where analysis happens, enabling seamless workflows for financial data retrieval and processing.

Developers working on financial applications, quantitative research, or trading tools should consider this project if they use Claude Code or Cursor as their primary development environment and need immediate access to market data without external API calls or context switching. The project is particularly suited for rapid prototyping of financial analysis scripts, backtesting workflows, and market research tasks. It works best for teams already invested in AI-assisted coding and seeking to reduce friction when incorporating market data into their work.

The project maintains active development with regular updates to its Skills collection. The codebase shows consistent refinement of existing tools and expansion of the financial data coverage. Development appears focused on ensuring reliability of market data integrations and expanding the range of supported asset classes and analysis workflows. The project demonstrates responsiveness to integration requirements across multiple AI coding platforms beyond its initial scope.