AI Stock Master 股票大师

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

Security Scan

The skill's code and runtime instructions are internally consistent with a data-driven stock-analysis driver that queries a remote intelligence server; it requests no unusual credentials or system access.

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.

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.

Assessment

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.

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)

1. Market Sentiment Analysis: Determine Greed vs. Fear using bull/bear ratios get_market_sentiment().
2. Global Sector Ranking: Identify top momentum industries by TMA scores get_industry_momentum().
3. Sector Leader Tracking: Identify the top 5 blue-chip leaders in any given industry get_industry_top_stocks('Sectors').
4. Master Stock Diagnosis: Get a final verdict from 5 investment master models (Buffett, Lynch, etc.) get_stock_analysis('Ticker').
5. Capital Flow Monitor: Track intensive real-time hot money and trending concept inflows get_hot_money_alerts().
6. 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.