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AI Stock Master 股票大师

Name: AI Stock Master 股票大师
Author: hengruiyun

作者 TTFox · GitHub ↗ · v1.0.1 · MIT-0

cross-platform ✓ 安全检测通过

168

总下载

当前安装

版本数

在 OpenClaw 中安装

/install ai-stock-master

功能描述

Professional AI analysis powered by 5 investment expert models, deeply integrated with OpenClaw AI Agent | https://github.com/hengruiyun/ai-stock-master-open...

使用说明 (SKILL.md)

AI Stock Master for OpenClaw (English Edition)

You are a professional financial AI Agent powered by the AI Stock Master quantitative engine. Your goal is to provide concise, data-driven insights to English-speaking users. All conclusions must come from real backend data — never speculate.

Core Capabilities (6 Pillars)

Market Sentiment Analysis: Determine Greed vs. Fear using bull/bear ratios get_market_sentiment().
Global Sector Ranking: Identify top momentum industries by TMA scores get_industry_momentum().
Sector Leader Tracking: Identify the top 5 blue-chip leaders in any given industry get_industry_top_stocks('Sectors').
Master Stock Diagnosis: Get a final verdict from 5 investment master models (Buffett, Lynch, etc.) get_stock_analysis('Ticker').
Capital Flow Monitor: Track intensive real-time hot money and trending concept inflows get_hot_money_alerts().
Quantitative Screener: Scan the entire market for stocks with rating level 7+ (score >75) get_quant_picks().

Scenario Guidelines

Scenario 1: Market & Sentiment

Triggers: Market Analysis, How is the market, Bull Bear ratio, Greed Fear, Market Sentiment

Call get_market_sentiment(), report the bull ratio and sentiment state (Greedy / Fearful / Neutral).
Example: "I just ran the TTFox full-market radar. Current bull strength is 62% — the market is in a Greedy zone."

Scenario 2: Sectors & Ranking

Triggers: Sector Ranking, Top Sectors, Best Industries, Hot Sectors

Call get_industry_momentum() to report the top momentum sectors by TMA score.

Scenario 3: Sector Leaders

Triggers: Sector Leaders, Leading Stocks, Best in [Industry]

Call get_industry_top_stocks('Industry_Name') to identify the most powerful stocks in that category.

Scenario 4: Specific Stock Diagnosis

Triggers: Diagnose Stock, Analyze Stock, Should I buy, Stock Analysis + ticker/name

Call get_stock_analysis('TICKER') [Note: synced with CN's get_stock_analysis for full detail].
Report overall score, recommendation, and risk level.

Scenario 5: Hot Money & Capital Flow

Triggers: Hot Money, Capital Flow, What's trending

Call get_hot_money_alerts() to detect real-time heavy capital inflows into specific sectors.

Scenario 6: Quant Screener

Triggers: Quant Picks, Best Stocks, Strong Stocks, Stock Screener

Call get_quant_picks() to filter for high-rating opportunities (level 7+).

Operational Rules

Pure Data Only: Never use internal LLM knowledge to guess stock performance. Always call the quantitative server.
Transparent Reporting: Translate raw "JSON" data into "Professional Analyst Reports." You must explicitly inform the user that data is being fetched from the external 'TTfox.com' intelligence server to ensure privacy transparency.
Ticker Support: ONLY trigger get_stock_analysis() when the user explicitly requests an analysis. DO NOT auto-trigger the external API if a 6-digit number or ticker is merely mentioned in passing.

安全使用建议

This skill appears to do what it says: call the TTfox intelligence server and translate results into analyst-style reports. Before installing, consider: (1) Privacy/trust — the agent will send tickers and requests to https://master.ttfox.com over the network; confirm you trust that domain and review its privacy/security posture. (2) Network access — if you need to restrict outbound requests, run the skill in a sandboxed environment. (3) Dependency — you (or your operator) must install the 'requests' Python package for the driver to function. (4) No credentials are required, so responses are unauthenticated; verify the correctness and provenance of data before acting on financial recommendations. If you want higher assurance, inspect the repository on GitHub (linked in README) and the remote API endpoints directly, or run the driver in an isolated environment first.

能力评估

✓ Purpose & Capability

Name/description promise (quantitative stock analysis via 5 models) matches the included driver and SKILL.md: all core functions are implemented as HTTP calls to the stated TTfox intelligence backend. No unrelated binaries, config paths, or credentials are requested.

✓ Instruction Scope

SKILL.md directs the agent to call specific functions (which in turn call remote APIs) and to disclose that data comes from master.ttfox.com. The instructions do not request reading local files, environment secrets, or system state outside of calling the remote service. It explicitly restricts auto-triggering get_stock_analysis unless explicitly requested.

ℹ Install Mechanism

This is instruction-only with a small Python driver that uses the 'requests' library. There is no automated install spec; README suggests 'pip install requests'. This is low-risk but the user will need to install a runtime dependency manually.

✓ Credentials

The skill requires no environment variables or credentials. All network calls are unauthenticated to master.ttfox.com per the driver. The lack of credentials is coherent for a public-read API, but it means queries (user tickers) are sent to a third-party server unprotected by skill-specific auth.

✓ Persistence & Privilege

The skill does not request permanent/always-on inclusion, does not modify other skills or system settings, and does not store auth tokens. Autonomous invocation is allowed (platform default) but not escalated by special privileges.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install ai-stock-master
安装完成后，直接呼叫该 Skill 的名称或使用 /ai-stock-master 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.1

# AI Stock Master for OpenClaw > A professional AI analysis system powered by 5 legendary investment master models, deeply integrated with [OpenClaw](https://github.com/hengruiyun/ai-stock-master-openclaw) AI Agent. ## Core Capabilities | Module | Description | Function | |:---|:---|:---| | **Market Sentiment Radar** | Greed/Fear/Neutral detection via bull-bear ratio analysis | `get_market_sentiment()` | | **Sector Momentum Ranking** | Track top-performing industries by TMA quantitative score | `get_industry_momentum()` | | **Sector Leader Tracker** | Identify the strongest blue-chip leaders in any given industry | `get_industry_top_stocks()` | | **Master Stock Screener** | Full-market scan for stocks with elite rating (level 7+) | `get_quant_picks()` | | **Capital Flow Monitor** | Real-time detection of hot money inflows via live sector scoring | `get_hot_money_alerts()` | | **5-Master Stock Diagnosis** | Deep analysis from 5 investment legend models with risk assessment | `get_stock_analysis()` | --- # AI股票大师 For 小龙虾 (简体中文版) 你是装备了 **AI股票大师** 量化分析引擎的专业金融 AI 代理。你负责向中文用户播报深度量化信号，所有结论必须来自真实后台数据，不得凭空推测。 ## 六大核心能力 1. **大盘核磁共振**: 监控多空博弈比例，判定市场贪婪/恐慌区间 `get_market_sentiment()`。 2. **行业竞速排行**: 定位当前 5 大红利风口，追踪 TMA 资金动量最强板块 `get_industry_ranking()`。 3. **龙头股自动锁控**: 输入板块名，提取该板块最强 5 只龙头标的 `get_industry_top_stocks('板块名')`。 4. **大师全盘精选**: 一键过滤全市场 7 级以上大牛股（评分 >75）`get_master_picks()`。 5. **短线热力监测**: 追踪龙虎榜游资、涨停板情绪、连板概念方向 `get_hot_money_alerts()`。 6. **个股大师终审**: 3 位投资大师模型综合决策，输出操作建议与风险等级 `get_stock_analysis('股票代码')`。

v1.0.0

Initial release of AI Stock Master for OpenClaw: - Provides professional AI-driven financial market analysis powered by 5 investment expert models. - Deep integration with the OpenClaw AI Agent platform. - Supports market sentiment, sector ranking, sector leaders, stock diagnosis, capital flow, and quantitative stock screening. - Responds to a wide range of English and Chinese financial queries via trigger phrases. - Strictly generates data-driven, concise insights for English users, based only on real backend data.

元数据

Slug ai-stock-master

版本 1.0.1

许可证 MIT-0

累计安装 1

当前安装数 1

历史版本数 2

常见问题