A collection of plug-and-play "skills" designed to transform AI agents into sophisticated financial analysts. It empowers LLMs with real-time news aggregation, stock data access, sentiment analysis, market prediction, and logic visualization capabilities, aiming for ease of integration and immediate utility for developers and power users.

How It Works

The project provides a modular suite of specialized skills that integrate with popular AI agent frameworks (e.g., Antigravity, OpenCode). Core functionalities include aggregating financial news from over 10 sources, accessing A-share and HK stock data, performing sentiment analysis via FinBERT/LLMs, and employing the Kronos model for news-aware market predictions. A key feature is the auto-generation of logic chain diagrams to visualize market impact.

Quick Start & Requirements

• Primary install command: npx skills add RKiding/Awesome-finance-skills@<skill-name> for individual skills, or manual cloning (git clone) and copying skills to agent directories.
• Prerequisites: Node.js (for npx), Git. Requires integration with compatible agent frameworks.
• Links: Live Demo (Free Lite Version): https://deepear.vercel.app/

Highlighted Details

• Aggregates real-time news from 10+ sources (e.g., Cailian, WSJ, Weibo, Polymarket).
• Features AI-powered predictions using the Kronos time-series forecasting model with news-aware adjustments.
• Includes a logic visualizer that auto-generates transmission chain diagrams (Draw.io XML output).
• Offers professional report generation capabilities, covering planning, writing, editing, and charting.

Maintenance & Community

No specific details regarding maintainers, community channels (e.g., Discord, Slack), or roadmap are provided in the README.

Licensing & Compatibility

The project is described as "open-source and free" ("开源免费"), but a specific license (e.g., MIT, Apache 2.0) is not explicitly stated. This lack of clarity may impact commercial use or integration into proprietary systems.

Limitations & Caveats

A specific software license is not declared, which could affect commercial adoption. The README does not detail unsupported platforms, known bugs, or performance benchmarks beyond feature claims. The "Free Lite Version" of the live demo suggests potential feature limitations in free offerings.