A comprehensive skill for financial stock analysis with technical indicators, real-time data fetching, chart generation, sentiment analysis, and multi-market support.

• Real-Time Data: Fetch current prices and historical data from multiple sources
• Chart Generation:
  • Visual Analysis: Generates professional candlestick charts with SMAs
  • Output: Returns a path to the chart image (PNG)
• Technical Analysis: 15+ indicators (RSI, MACD, Bollinger Bands, Moving Averages, etc.)
• Trading Signals: Automated buy/sell/hold recommendations based on technical indicators
• Sentiment Analysis:
  • Headlines: Latest news events
  • Scores: Polarity (-1 to 1) and Subjectivity for each headline and an average for the stock
• Financial Health: Market Cap, PE Ratio, Revenue, Net Income
• Multi-Market Support: US stocks, Hong Kong stocks (.HK), China A-shares (.SS, .SZ)
• Data Caching: Automatic caching to reduce API calls and improve response time

Trend Indicators:

• Simple Moving Averages (SMA): 20, 50, 200-day
• Exponential Moving Averages (EMA): 12, 26-day
• MACD (Moving Average Convergence Divergence)
• ADX (Average Directional Index)

Momentum Indicators:

• RSI (Relative Strength Index)
• Stochastic Oscillator (%K, %D)
• CCI (Commodity Channel Index)
• ROC (Rate of Change)

Volatility Indicators:

• Bollinger Bands (Upper, Middle, Lower, Bandwidth)
• ATR (Average True Range)
• Standard Deviation

Volume Indicators:

• OBV (On-Balance Volume)
• VWAP (Volume Weighted Average Price)

The skill generates the following signals:

• RSI Signal: Overbought (>70), Oversold (<30), Neutral
• MACD Signal: Bullish, Bearish, Neutral
• Bollinger Bands Signal: Overbought, Oversold, Normal
• Trend Signal: Strong Uptrend, Uptrend, Downtrend, Strong Downtrend, Sideways
• Stochastic Signal: Overbought, Oversold, Neutral
• Volume Signal: High, Low, Normal
• Overall Recommendation: Strong Buy, Buy, Hold, Sell, Strong Sell

When a user requests stock analysis, follow this workflow:

Basic price queries:

• "What's AAPL trading at?" → Run: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker AAPL
• "Show me Tesla's price" → Run: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker TSLA

Technical analysis queries:

• "Is AAPL overbought?" → Run: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker AAPL --technical
• "Analyze TSLA with technical indicators" → Run: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker TSLA --technical
• "Should I buy MSFT?" → Run: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker MSFT --technical

Chart generation queries:

• "Show me a chart of AAPL" → Run script with chart option, display the image from data['chart'] field
• "Chart for NVDA" → Generate candlestick chart and embed using ![Chart](<path>)

Sentiment analysis queries:

• "What is the sentiment for Tesla?" → Run script and report data['news_sentiment'] values
• "How is the news for NVDA?" → Analyze sentiment scores and describe market mood

Historical data queries:

• "Show me AAPL's 6-month trend" → Run: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker AAPL --period 6mo --technical

Multi-market queries:

• "Analyze Tencent stock" → Run: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker 0700.HK --technical
• "How is Moutai performing?" → Run: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker 600519.SS --technical

The script returns structured JSON with the following format:

{
  "metadata": {
    "ticker": "AAPL",
    "market": "us",
    "timestamp": "2026-01-07T10:30:00Z",
    "currency": "USD",
    "cached": false
  },
  "price": {
    "current": 185.23,
    "change": 0.73,
    "change_pct": 0.40,
    "open": 184.50,
    "high": 186.00,
    "low": 183.75,
    "volume": 52341000
  },
  "technical": {
    "indicators": {
      "rsi_14": 62.5,
      "macd": {"macd": 2.34, "signal": 1.89, "histogram": 0.45},
      "bb_upper": 190.50,
      "bb_middle": 185.00,
      "bb_lower": 179.50,
      "sma_20": 183.20,
      "sma_50": 182.34,
      "sma_200": 175.67
    },
    "signals": {
      "rsi_signal": "neutral",
      "macd_signal": "bullish",
      "bb_signal": "normal",
      "trend": "uptrend",
      "recommendation": "buy"
    }
  },
  "chart": "/path/to/chart.png",
  "news_sentiment": {
    "average_polarity": 0.45,
    "average_subjectivity": 0.62,
    "headlines": [...]
  },
  "history": [...]
}

Based on the data returned:

For price-only queries:

• State current price, change, and change percentage
• Mention if data is cached (check metadata.cached)

For technical analysis queries:

• Interpret key indicators relevant to the question
• Explain what the signals mean
• Provide the overall recommendation
• Support your analysis with specific indicator values

For chart queries:

• Display the chart: The JSON output includes a "chart" field with a file path. You must display this image to the user using markdown: ![Chart](<path>)
• Describe key visual patterns visible in the chart

For sentiment queries:

• Use the values in "news_sentiment" to describe market mood
• Report average polarity and subjectivity
• Mention key headlines if relevant

Example interpretation:

User: "Is AAPL overbought right now?"

[After running the command and getting JSON output]

Response: "Apple (AAPL) is currently trading at $185.23, up 0.40% today. Based on technical analysis:

- RSI is at 62.5, which is in neutral territory (not overbought). Overbought would be above 70.
- The price is near the middle Bollinger Band at $185.00, suggesting normal volatility.
- MACD shows a bullish signal with a positive histogram of 0.45.
- The stock is in an uptrend, trading above its 50-day SMA of $182.34.

Overall recommendation: BUY. The stock shows bullish momentum without being overextended."

The skill automatically detects the market from the ticker format:

• US Stocks: Use standard ticker (AAPL, TSLA, MSFT)
• Hong Kong Stocks: Use .HK suffix (0700.HK for Tencent, 9988.HK for Alibaba)
• China A-Shares:
  • Shanghai: .SS suffix (600519.SS for Moutai)
  • Shenzhen: .SZ suffix (000001.SZ for Ping An Bank)

The system automatically adjusts timezone and currency based on the market.

# Basic price check
python3 main.py --ticker AAPL

# Technical analysis
python3 main.py --ticker AAPL --technical

# Custom time period (1mo, 6mo, 1y, max)
python3 main.py --ticker AAPL --period 3mo --technical

# Custom interval (1d, 1wk, 1mo)
python3 main.py --ticker AAPL --period 6mo --interval 1d

# Disable caching (force fresh data)
python3 main.py --ticker AAPL --technical --no-cache

1. Always use ${CLAUDE_PLUGIN_ROOT} - This environment variable points to the correct plugin directory
2. Check for errors - If the JSON contains an error field, explain the error to the user
3. Cache awareness - Mention if data is cached (metadata.cached = true) when relevant
4. Market context - Include market name and currency in your response
5. Be specific - Cite actual indicator values from the JSON, don't make up numbers
6. Explain signals - Don't just state "RSI is 62.5", explain what that means ("RSI at 62.5 indicates neutral momentum, neither overbought nor oversold")
7. Display charts - When chart data is available, always embed the image in your response
8. Report sentiment - Include news sentiment analysis when available in the data

If the command fails or returns an error:

1. Check the error message in the JSON output
2. Common issues:
   • Invalid ticker symbol
   • Market closed (recent data may not be available)
   • API rate limits (try again with --no-cache)
   • Network issues
3. Explain the error clearly to the user
4. Suggest alternatives if possible

Example 1: Basic Price Check

User: "What's the current price of Apple stock?"

Command: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker AAPL

Response: "Apple (AAPL) is currently trading at $185.23 USD, up $0.73 (0.40%) today."

Example 2: Technical Analysis

User: "Should I buy Tesla stock?"

Command: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker TSLA --technical

Response: "Tesla (TSLA) is trading at $235.50. Based on technical analysis:
- RSI: 45.2 (neutral - neither overbought nor oversold)
- MACD: Bullish signal (histogram: +1.23)
- Trend: Uptrend (price above 50-day SMA)
- Bollinger Bands: Trading in normal range

Overall recommendation: BUY. The stock shows bullish momentum with neutral RSI, suggesting room for upside without being overextended."

Example 3: Chart Generation

User: "Show me a chart of AAPL"

Command: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker AAPL

Response: "Here's the candlestick chart for Apple (AAPL):
![Chart](/path/to/chart.png)

The chart shows recent price action with 50-day and 200-day moving averages overlaid."

Example 4: Sentiment Analysis

User: "What is the sentiment for Tesla?"

Command: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker TSLA

Response: "Tesla (TSLA) news sentiment analysis:
- Average Polarity: 0.45 (Positive)
- Average Subjectivity: 0.62 (Moderately Subjective)

Recent headlines show a generally positive sentiment toward Tesla, indicating favorable market perception."

Example 5: Hong Kong Stock

User: "Analyze Tencent stock"

Command: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker 0700.HK --technical

Response: "Tencent Holdings (0700.HK) is trading at 385.00 HKD in the Hong Kong market..."

Example 6: Historical Trend

User: "How has Microsoft performed over the last 6 months?"

Command: python3 ${CLAUDE_PLUGIN_ROOT}/skills/stock-analyzer/scripts/main.py --ticker MSFT --period 6mo --technical

Response: "Microsoft (MSFT) is currently at $420.15. Over the past 6 months:
- Strong uptrend: Price well above 200-day SMA ($380.25)
- RSI at 68: Approaching overbought but still in bullish territory
- MACD: Positive and rising
The stock has gained approximately 11% over the 6-month period, showing consistent upward momentum."

• Primary: yfinance library (Yahoo Finance data)
• Fallback: Direct Yahoo Finance API
• Cache: Local file-based cache (15-minute TTL)

• Real-time data has ~15-minute delay for free tier
• Some indicators require minimum data history (e.g., 200-day SMA needs 200 days)
• Market-specific data availability varies (US > HK > CN A-shares)
• Technical analysis is based on historical data and doesn't guarantee future performance