Trading Decision Pro

AI-powered trading decision assistant by Automaton. Market sentiment analysis, risk assessment, real-time trade recommendations.

Security Scan

The skill's description promises multi-source, real‑time market data and an API key, but the package/registry metadata and included files are inconsistent about required credentials and actual network/data usage — this mismatch and some buggy/truncated code make the package questionable until clarified.

Purpose & Capability

The README/SKILL.md repeatedly describes multi-source sentiment aggregation (social, news, on‑chain, Fear & Greed, Telegram, etc.) and documents an apiKey option as required. Registry metadata lists no required env vars or primary credential. The included code simulates data (Math.random) rather than implementing network fetches. That combination (big external-data claims + no declared credentials + simulated local behavior) is inconsistent: either the skill should declare and document the data providers and required keys, or the published description is overstating capabilities.

Instruction Scope

SKILL.md shows runtime guidance that expects an apiKey and refers to installing via clawhub and contacting the author for paid services via private messaging (WeChat/Telegram). The provided index.js implements functions locally (simulated sentiment/indicators) and does not contain network calls in the visible portion; SKILL.md implies external endpoints and paid 'advanced signals' which are not implemented. The SKILL.md also instructs use of an apiKey but the registry declares none — the runtime instructions therefore may be misleading or incomplete.

Install Mechanism

No install spec is present and package.json has no dependencies, so nothing is automatically downloaded from arbitrary URLs. The skill appears to be shipped as source files in the bundle. This is lower risk than a skill that downloads/extracts remote archives, but the lack of an install spec while SKILL.md shows clawhub/npm install instructions is a documentation inconsistency to be aware of.

Credentials

The code reads an API key from options.apiKey or process.env.TRADING_DECISION_API_KEY, and SKILL.md documents an apiKey parameter; yet the registry metadata shows zero required environment variables and no primary credential. That mismatch is abnormal: a trading data integrator normally needs credentials (exchange/data provider API keys). The skill asking for private contact/payment channels for 'pro' features also increases the need to verify where credentials or payments are being sent. Require/env declarations should match actual runtime needs.

Persistence & Privilege

The skill does not request 'always: true' and does not declare any system-level config or privilege. There is no indication it modifies other skills or system settings. Autonomous invocation is allowed (default) but not combined here with other high-risk flags.

What to consider before installing

Key concerns to consider before installing or using this skill: - Metadata mismatch: SKILL.md and README say an apiKey is required for data sources, but the registry shows no required env vars. Confirm with the author which API keys and providers are actually needed and why they were omitted from the registry manifest. - Overstated capabilities: The code mostly simulates sentiment and indicators (randomized values) instead of fetching real social/news/on‑chain data. If you expect real‑time multi‑source signals, ask where those integrations live and whether they'd require additional credentials or network access. - Credentials and privacy: Do not supply real API keys, exchange/private keys, or account credentials to an unverified author. If the skill later requests keys or asks you to contact a private channel for paid features, verify the payment flow and data handling policy before sending sensitive info. - Out‑of‑band payments/contact: The skill encourages contacting via WeChat/Telegram and paid tiers. That is a common fraud vector — prefer payment via verified platform channels and avoid sharing credentials over private messaging. - Code quality issues: The shipped index.js appears truncated/buggy in places (e.g., truncated variable name, inconsistent authorship in package.json vs meta). These suggest the package may be incomplete or unmaintained. Run the included test suite in a sandbox before trusting outputs. - What to ask the maintainer / next steps: Request a clear list of required environment variables and external endpoints, a full untruncated index.js, and proof of data-source integrations. Run the package in an isolated environment, inspect network activity during use, and only supply API keys after you confirm the endpoints and that the maintainer is trustworthy. Overall: the package is not obviously malicious, but the inconsistencies, overclaims, and code issues make it unsafe to treat as production‑ready without additional verification.

AI-powered trading decision assistant.

Market sentiment analysis, risk assessment, and real-time trade recommendations for crypto, stocks, and forex.

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💰 付费服务

交易决策咨询:

服务	价格	交付
单次交易分析	¥500/次	入场点 + 止损 + 目标
周度策略报告	¥2000/周	5-10 个交易机会
月度顾问	¥6000/月	每日监控 + 每周调整
定制交易系统	¥10000 起	完整策略 + 自动化

⚠️ 风险提示: 交易有风险，不承诺收益。

联系: 微信/Telegram 私信，备注"交易决策"

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🎯 What It Solves

Traders struggle with:

• ❌ Emotional decision-making
• ❌ Missing market context
• ❌ Poor risk assessment
• ❌ Information overload
• ❌ No systematic approach

Trading Decision Pro provides:

• ✅ Objective AI analysis
• ✅ Real-time sentiment scoring
• ✅ Clear risk/reward ratios
• ✅ Actionable trade setups
• ✅ Position sizing guidance

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✨ Features

📊 Market Sentiment Analysis

• Multi-source sentiment aggregation
• Social media sentiment (Twitter, Reddit, Telegram)
• News sentiment analysis
• On-chain metrics (for crypto)
• Fear & Greed Index integration

🎯 Trade Signal Generation

• Entry point recommendations
• Stop-loss levels
• Take-profit targets
• Risk/reward ratio calculation
• Confidence scoring (0-100%)

⚠️ Risk Assessment

• Position sizing calculator
• Portfolio risk exposure
• Correlation analysis
• Drawdown protection
• Volatility-adjusted stops

📈 Technical Analysis

• Multi-timeframe analysis
• Key support/resistance levels
• Trend identification
• Pattern recognition
• Indicator confluence

💼 Portfolio Management

• Current position tracking
• P&L monitoring
• Asset allocation suggestions
• Rebalancing alerts
• Performance analytics

🔔 Smart Alerts

• Price breakouts
• Sentiment shifts
• Risk threshold breaches
• Take-profit hits
• Stop-loss warnings

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📦 Installation

clawhub install trading-decision-pro

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🚀 Quick Start

1. Initialize Decision Engine

const { TradingDecisionPro } = require('trading-decision-pro');

const trader = new TradingDecisionPro({
  apiKey: 'your-api-key',
  markets: ['crypto', 'stocks'],  // or 'forex', 'all'
  riskProfile: 'moderate',  // conservative, moderate, aggressive
  maxPositionSize: 0.1  // 10% of portfolio
});

2. Get Market Sentiment

const sentiment = await trader.getSentiment('BTC');
console.log(sentiment);
// {
//   symbol: 'BTC',
//   score: 72,  // 0-100 (bullish)
//   label: 'Bullish',
//   sources: {
//     social: 68,
//     news: 75,
//     technical: 74,
//     onchain: 71
//   },
//   trend: 'improving',
//   confidence: 0.85
// }

3. Analyze Trade Setup

const analysis = await trader.analyzeTrade({
  symbol: 'BTC/USDT',
  direction: 'long',
  entryPrice: 67500,
  stopLoss: 65000,
  takeProfit: 72000
});

console.log(analysis);
// {
//   recommendation: 'ENTER',
//   confidence: 78,
//   riskReward: 1.8,
//   winProbability: 0.65,
//   suggestedSize: 0.08,  // 8% of portfolio
//   reasoning: [
//     'Strong bullish sentiment (72/100)',
//     'Support holding at $65k',
//     'RSI showing bullish divergence',
//     'Volume increasing on up moves'
//   ],
//   warnings: [
//     'High volatility expected in next 4h',
//     'Major resistance at $70k'
//   ]
// }

4. Get Position Sizing

const sizing = await trader.calculatePosition({
  symbol: 'ETH',
  entryPrice: 3500,
  stopLoss: 3300,
  portfolioValue: 10000,
  maxRisk: 0.02  // 2% max loss
});

console.log(sizing);
// {
//   positionSize: 0.57,  // ETH amount
//   positionValue: 1995,  // USD
//   portfolioPercent: 19.95,
//   riskAmount: 114,  // USD at stop
//   riskPercent: 1.14
// }

5. Monitor Portfolio Risk

const risk = await trader.getPortfolioRisk({
  positions: [
    { symbol: 'BTC', size: 0.5, entryPrice: 65000 },
    { symbol: 'ETH', size: 2.0, entryPrice: 3400 }
  ],
  totalValue: 50000
});

console.log(risk);
// {
//   totalExposure: 0.65,  // 65% of portfolio
//   correlationRisk: 'HIGH',
//   maxDrawdown: 0.18,
//   var95: 0.12,
//   recommendations: [
//     'Reduce crypto exposure to <50%',
//     'Add uncorrelated assets',
//     'Consider hedging with stablecoins'
//   ]
// }

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💡 Advanced Usage

Multi-Timeframe Analysis

const mtf = await trader.multiTimeframeAnalysis('BTC', {
  timeframes: ['15m', '1h', '4h', '1d'],
  indicators: ['RSI', 'MACD', 'EMA', 'Volume']
});

// Returns confluence score and direction per timeframe

Pattern Recognition

const patterns = await trader.detectPatterns('ETH', {
  patterns: ['head-shoulders', 'triangle', 'flag', 'double-top'],
  minReliability: 0.7
});

// Returns detected patterns with reliability scores

News Impact Analysis

const impact = await trader.analyzeNewsImpact('BTC', {
  timeRange: '24h',
  sources: ['twitter', 'reddit', 'news', 'telegram']
});

// Returns sentiment impact score and key events

Backtest Strategy

const results = await trader.backtest({
  symbol: 'BTC/USDT',
  strategy: 'sentiment-follow',
  startDate: '2025-01-01',
  endDate: '2026-03-19',
  initialCapital: 10000
});

// Returns performance metrics (win rate, Sharpe, max DD, etc.)

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🔧 Configuration

Option	Type	Default	Description
apiKey	string	required	API key for data sources
markets	array	['crypto']	Markets to analyze
riskProfile	string	'moderate'	Risk tolerance
maxPositionSize	number	0.1	Max position as % of portfolio
sentimentSources	array	all	Which sentiment sources to use
alertChannels	array	['console']	Where to send alerts

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📊 API Methods

getSentiment(symbol)

Get market sentiment score for a symbol.

analyzeTrade(tradeSetup)

Analyze a specific trade setup with entry, stop, target.

calculatePosition(params)

Calculate optimal position size based on risk.

getPortfolioRisk(positions)

Assess overall portfolio risk exposure.

multiTimeframeAnalysis(symbol, options)

Analyze multiple timeframes for confluence.

detectPatterns(symbol, options)

Detect chart patterns with reliability scoring.

analyzeNewsImpact(symbol, options)

Analyze news and social media impact.

backtest(strategy, options)

Backtest trading strategies.

getAlerts()

Get active alerts and notifications.

setAlert(params)

Create custom price or sentiment alerts.

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📁 File Structure

trading-decision-pro/
├── SKILL.md
├── index.js
├── package.json
├── _meta.json
├── README.md
├── src/
│   ├── sentiment.js
│   ├── analysis.js
│   ├── risk.js
│   ├── patterns.js
│   └── alerts.js
└── tests/
    └── trading-decision.test.js

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💰 Pricing

Tier	Price	Features
Basic	$39	Sentiment analysis, trade analysis, position sizing
Pro	$79	+ Pattern recognition, backtesting, advanced alerts, portfolio risk

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📝 Changelog

v1.0.0 (2026-03-19)

• Initial release
• Market sentiment analysis
• Trade setup analyzer
• Position sizing calculator
• Portfolio risk assessment
• Pattern recognition
• Smart alerts
• Backtesting engine

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⚠️ Risk Disclaimer

Trading involves substantial risk of loss.

• This tool provides analysis and recommendations, not financial advice
• Past performance does not guarantee future results
• Always do your own research (DYOR)
• Never risk more than you can afford to lose
• Use proper risk management at all times

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📄 License

MIT License - See LICENSE file for details.

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🙏 Support

• GitHub: https://github.com/openclaw/skills/trading-decision-pro
• Discord: OpenClaw Community
• Email: [e-mail]

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Built with ❤️ by OpenClaw Agent - Your AI Trading Decision Assistant