TradingAgents‑AShare: Multi‑Agent AI for Real‑Time Stock Research
From the repo · “A 股多智能体智能投研系统 — 基于 TradingAgents 架构,15 名 AI Agent 模拟机构协作与实时辩论对抗,全流程可视化,支持 OpenClaw / Claude Code 集成,Docker 一键部署。”
TradingAgents-AShare is an AI-powered trading research system that simulates the collaboration and debate of 15 AI agents to provide intelligent investment insights
- •When you need to analyze and visualize the behavior of multiple AI agents in a trading scenario
- •When you want to integrate AI-powered trading research with existing systems using OpenClaw or Claude Code
- •When you need a scalable and deployable solution for trading research using Docker
docker run -it --rm -v $(pwd):/app kylinmountain/tradingagents-ashare:latest python app.py --mode train --agent-count 15 --episode-count 100
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Works after you add credentials — the setup agent will ask you for them.
mkdir -p ~/.claude/skills/tradingagents-ashare && curl -fsSL https://workflowstacks.com/api/skills/tradingagents-ashare/claude-skill -o ~/.claude/skills/tradingagents-ashare/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
TradingAgents‑AShare: Multi‑Agent AI for Real‑Time Stock Research is a large Python project (~35k lines across 145 code files, plus 27 test files). Setup is light: installs like a normal app — add your API keys. Reading the code is optional. Last commit this month, Other license, has a test suite.
- 1README.mdStart here — what it does and how to install it
- 2api/main.pyWhere the program starts running
- 3pyproject.tomlDependencies and the commands it exposes
- 4.env.exampleThe API keys and settings you must provide
- 5skills/tradingagents-analysis/SKILL.mdInside skills/ — an example of what the AI is told to do
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Works after you add credentials — the setup agent will ask you for them.
mkdir -p ~/.claude/skills/tradingagents-ashare && curl -fsSL https://workflowstacks.com/api/skills/tradingagents-ashare/claude-skill -o ~/.claude/skills/tradingagents-ashare/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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Do this with a working workflow
Pages we wrote and tested that put a skill like this to work — importable n8n templates, outcome guides and Claude Desktop configs.
Context7 (live docs) MCP config
Pull up-to-date library docs into Claude so it codes against the real API.
Outcome guideScore your leads by ideal-customer fit
You describe your ideal customer once and keep leads in a Google Sheet. The workflow scores each 1–5 for fit with a one-line reason, so you sort and work the best first.
MCP configPlaywright (browser) MCP config
Drive a real browser for testing and automation from Claude.
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