trading-agents

name trading-agents description Multi-agent stock trading signal analysis framework with two-round debate mechanism. Triggered when users provide a stock ticker for investment analysis. Input a stock ticker, analyze through 7 SubAgents in 4 layers (Information Gathering → Opinion Formation → Two-Round Debate → Final Decision), output BUY/SELL/HOLD recommendation with rationale. Trigger phrases: "analyze this stock", "give me investment advice", "is this stock worth buying", "analyze XX stock", "stock investment analysis". TradingAgents - Stock Trading Signal Analysis Assistant Multi-agent collaborative stock trading signal analysis framework with two-round debate mechanism , inspired by the open-source TradingAgents project. Environment Requirements Required Environment Variables Variable Required Description TUSHARE_TOKEN ✅ Tushare Pro API Token, get at: https://tushare.pro/register BRAVE_API_KEY ⚪ Brave Search API Key (optional, for news search enhancement) Python Dependencies Install required packages before using this skill: pip install tushare>=1.3.0 pandas>=1.5.0 numpy>=1.21.0 Secure Configuration Security Warning : Do NOT paste your API tokens in chat messages. Set Environment Variables Before running this skill, ensure the following environment variables are set: export TUSHARE_TOKEN=your_token_here export BRAVE_API_KEY=your_brave_key_here # optional Avoid : Do NOT add tokens to ~/.bashrc , ~/.zshrc , or other shell config files Do NOT include tokens in reports or SubAgent communications Do NOT paste tokens in chat messages Side Effects This skill will: Write reports to ~/.openclaw/workspace/memory/reports/trading-agents-*.md Connect to Tushare Pro API ( api.tushare.pro ) Use web_search for news and sentiment data No data is transmitted externally beyond these API calls. Security Rules Credential Protection Only read TUSHARE_TOKEN and BRAVE_API_KEY from environment variables Never read other configuration files (e.g., openclaw.json, .bashrc, etc.) Never include API keys or tokens in: SubAgent inter-communications Generated reports Any output files Report Content Rules All generated reports and SubAgent communications MUST NOT contain: API keys (TUSHARE_TOKEN, BRAVE_API_KEY) Passwords or secrets Any credential values If a SubAgent receives or generates content containing sensitive credentials, it must redact them before passing to other agents or writing to files. Workflow (4-Layer Architecture) Input: Stock Ticker (e.g., 300750.SZ) ↓ ┌─────────────────────────────────────────────────────┐ │ Layer 1: Information Gathering (Parallel) │ │ ├─ SubAgent 1: Fundamental Analyst │ │ ├─ SubAgent 2: Market Analyst │ │ ├─ SubAgent 3: News Analyst │ │ └─ SubAgent 4: Social Media Analyst │ └─────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────┐ │ Layer 2: Opinion Formation (Parallel) │ │ ├─ SubAgent 5: Bull Researcher (Initial Report) │ │ └─ SubAgent 6: Bear Researcher (Initial Report) │ └─────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────┐ │ Layer 2.5: Two-Round Debate (Sequential) │ │ ├─ Round 1: │ │ │ ├─ Bear Researcher → Bull's Arguments │ │ │ └─ Bull Researcher → Bear's Arguments │ │ └─ Round 2: │ │ ├─ Bear Researcher → Bull's Rebuttals │ │ └─ Bull Researcher → Bear's Rebuttals │ └─────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────┐ │ Layer 3: Final Decision │ │ └─ SubAgent 7: Research Manager │ │ (Synthesizes all reports + debate history) │ └─────────────────────────────────────────────────────┘ ↓ Output: BUY/SELL/HOLD + Investment Plan (Markdown) Step 7: Export to Markdown Report Research Manager outputs the complete report to a markdown file: ~/.openclaw/workspace/memory/reports/trading-agents-[stock_code]-[timestamp].md The markdown file contains: Part I: Final Investment Decision Part II: Layer 1 Reports (4 reports) Part III: Layer 2 Reports (2 initial reports) Part IV: Debate History (4 responses) Part V: Appendix Execution Steps Step 1: Parse Stock Ticker Extract stock ticker from user input, format to standard: A-shares: 600519.SH , 300750.SZ HK stocks: 00700.HK US stocks: AAPL Step 2: Execute Layer 1 SubAgents in Parallel Use sessions_spawn to launch in parallel 4 SubAgents: SubAgent Task Output Fundamental Analyst Fundamental analysis Fundamental report Market Analyst Market technical analysis Market analysis report News Analyst News analysis News summary report Social Media Analyst Social sentiment analysis Sentiment report Step 3: Collect Layer 1 Reports Use subagents(action=list) to check all SubAgent completion status, then collect report content. Step 4: Execute Layer 2 SubAgents in Parallel (Initial Reports) Pass Layer 1 reports to Layer 2, launch in parallel 2 SubAgents: SubAgent Task Input Output Bull Researcher Initial bull report Layer 1 4 reports Bull report (initial) Bear Researcher Initial bear report Layer 1 4 reports Bear report (initial) Step 5: Two-Round Debate After Layer 2 completes, initiate two rounds of debate : Round 1: Bear Researcher receives Bull's initial report → Refutes bull arguments Bull Researcher receives Bear's initial report → Refutes bear arguments Round 2: Bear Researcher receives Bull's Round 1 rebuttals → Counter-rebuttal Bull Researcher receives Bear's Round 1 rebuttals → Counter-rebuttal Debate Rules : Use specific data and reasoning to refute opponent's arguments Cite sources from all available reports Apply conversational debate style Reflect on past experience and lessons learned Each response should directly address opponent's specific points Never include API keys or tokens in debate content Step 6: Execute Final Decision SubAgent Launch Research Manager with ALL inputs: Layer 1: 4 reports (Fundamental, Market, News, Social) Layer 2: 2 initial reports (Bull, Bear) Layer 2.5: 4 debate responses (Round 1 + Round 2) Research Manager synthesizes all information and makes final investment recommendation. SubAgent Details SubAgent 1: Fundamental Analyst Data Sources : Tushare Pro API (financial data, valuation metrics) Company annual/quarterly reports Analysis Dimensions : Financial statement analysis Valuation metrics (PE/PB/PS percentile) Growth metrics Company basic information Shareholder structure Detailed Prompt : See references/fundamental-analyst.md SubAgent 2: Market Analyst Data Sources : Tushare Pro API (daily data) Technical indicator calculations Analysis Dimensions : Price trend (MA system) Technical indicators (MACD, RSI, KDJ, BOLL) Volume analysis Capital flow Market anomaly signals Detailed Prompt : See references/market-analyst.md SubAgent 3: News Analyst Data Sources : Web Search (Brave Search API) Financial media websites Analysis Dimensions : Company news Industry news Management dynamics Macro news Detailed Prompt : See references/news-analyst.md SubAgent 4: Social Media Analyst Data Sources : Web Search Xueqiu, Guba, Weibo, Zhihu, etc. Analysis Dimensions : Sentiment heat Investor sentiment (bullish/bearish ratio) Controversy focus KOL opinions Detailed Prompt : See references/social-analyst.md SubAgent 5: Bull Researcher Role : Bull analyst advocating for investment Tasks : Generate initial bull report from Layer 1 data Refute bear's arguments in debate rounds Provide counter-rebuttals in Round 2 Debate Style : Conversational tone addressing opponent directly Use specific data to counter opponent's points Cite sources from all available reports Reflect on past experience and mistakes Never include API keys in output Detailed Prompt : See references/bull-researcher.md SubAgent 6: Bear Researcher Role : Bear analyst advocating against investment Tasks : Generate initial bear report from Layer 1 data Refute bull's arguments in debate rounds Provide counter-rebuttals in Round 2 Debate Style : Conversational tone addressing opponent directly Use specific data to expose weaknesses Cite sources from all available reports Reflect on past experience and mistakes Never include API keys in output Detailed Prompt : See references/bear-researcher.md SubAgent 7: Research Manager Role : Portfolio manager making final decision Input (9 items total): Fundamental Analysis Report Market Analysis Report News Analysis Report Social Media Sentiment Report Bull Initial Report Bear Initial Report Round 1 Debate (2 responses) Round 2 Debate (2 responses) Responsibilities : Synthesize all reports and debate history Identify most persuasive arguments from both sides Make final decision: BUY/SELL/HOLD Develop detailed investment plan Ensure final report contains NO API keys or tokens Important : Do not default to "HOLD" - must take a stance based on strongest arguments. Detailed Prompt : See references/research-manager.md Report Format Requirements Price Change Color Convention (China Style) Red = Up (+) Green = Down (-) Data Citation All data must cite sources When using Tushare Pro, note Data Source: Tushare Pro When using Web Search, cite source URL Security Requirement Reports MUST NOT contain any API keys, tokens, or credentials If any credential is found in output, redact immediately Signature Use signature at end of financial reports Implementation Scripts Get Fundamental Data python3 scripts/get_fundamentals.py <stock_code> Get Market Data python3 scripts/get_market_data.py <stock_code> Output Example # TradingAgents Investment Decision Report: 宁德时代 (300750.SZ) Report Generated: YYYY-MM-DD HH:MM Framework Version: TradingAgents v2.0 with Debate Mechanism --- # Part I: Final Investment Decision ## 一、决策摘要 ### 投资建议 # 🟢 买入 / 🔴 卖出 / 🟡 持有 ### 核心理由 [一句话概括核心理由，基于辩论结果] ### 信心指数 | 维度 | 信心度 | 说明 | |------|:------:|------| | 基本面 | x/5 | [说明] | | 市场面 | x/5 | [说明] | | 消息面 | x/5 | [说明] | | 综合信心 | x/5 | - | --- ## 二、辩论精华回顾 ### 2.1 初始观点对比 | 方面 | 看涨观点 | 看跌观点 | |------|----------|----------| | 核心论点 | [论点] | [论点] | | 支撑数据 | [数据] | [数据] | | 初始得分 | x/5 | x/5 | ### 2.2 第一轮辩论结果 #### 看跌方对看涨方的挑战 | 看涨论点 | 看跌方反驳 | 反驳有效性 | 幸存状态 | |----------|------------|:----------:|:--------:| | [论点1] | [反驳] | 高/中/低 | ✅/❌ | | [论点2] | [反驳] | 高/中/低 | ✅/❌ | #### 看涨方对看跌方的挑战 | 看跌论点 | 看涨方反驳 | 反驳有效性 | 幸存状态 | |----------|------------|:----------:|:--------:| | [论点1] | [反驳] | 高/中/低 | ✅/❌ | | [论点2] | [反驳] | 高/中/低 | ✅/❌ | ### 2.3 第二轮辩论结果 | 议题 | 看涨最终立场 | 看跌最终立场 | 辩论胜出方 | |------|--------------|--------------|:----------:| | [议题1] | [立场] | [立场] | 🟢/🔴/🟡 | | [议题2] | [立场] | [立场] | 🟢/🔴/🟡 | ### 2.4 辩论胜负关键 **看涨方胜出理由** (如适用): 1. [理由1] 2. [理由2] **看跌方胜出理由** (如适用): 1. [理由1] 2. [理由2] --- ## 三、最终判断 ### 3.1 为什么选择 [买入/卖出/持有] [详细解释基于辩论结果做出此决策的原因] ### 3.2 经过辩论验证的核心论点