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Technical Analysis

skill-staskh-trading-skills-technical-analysis · by staskh

Compute technical indicators like RSI, MACD, Bollinger Bands, SMA, EMA for a stock. Use when user asks about technical analysis, indicators, RSI, MACD, moving averages, overbought/oversold, or chart analysis.

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Install

$ agentstack add skill-staskh-trading-skills-technical-analysis

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

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About

Technical Analysis

Compute technical indicators using pandas-ta. Supports multi-symbol analysis and earnings data.

Instructions

> Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/technicals.py SYMBOL [--period PERIOD] [--indicators INDICATORS] [--earnings]

Arguments

  • SYMBOL - Ticker symbol or comma-separated list (e.g., AAPL or AAPL,MSFT,GOOGL)
  • --period - Historical period: 1mo, 3mo, 6mo, 1y (default: 3mo)
  • --indicators - Comma-separated list: rsi,macd,bb,sma,ema,atr,adx (default: all)
  • --earnings - Include earnings data (upcoming date + history)

Output

Single symbol returns:

  • price - Current price and recent change
  • indicators - Computed values for each indicator
  • risk_metrics - Volatility (annualized %) and Sharpe ratio
  • signals - Buy/sell signals based on indicator levels
  • earnings - Upcoming date and EPS history (if --earnings)

Multiple symbols returns:

  • results - Array of individual symbol results

Interpretation

  • RSI > 70 = overbought, RSI SMA50) = bullish
  • ADX > 25 = strong trend
  • Sharpe ratio > 1 = good risk-adjusted returns, > 2 = excellent
  • Volatility (annualized) = standard deviation of returns scaled to annual basis

Examples

# Single symbol with all indicators
uv run python scripts/technicals.py AAPL

# Multiple symbols
uv run python scripts/technicals.py AAPL,MSFT,GOOGL

# With earnings data
uv run python scripts/technicals.py NVDA --earnings

# Specific indicators only
uv run python scripts/technicals.py TSLA --indicators rsi,macd

Correlation Analysis

Compute price correlation matrix between multiple symbols for diversification analysis.

Instructions

uv run python scripts/correlation.py SYMBOLS [--period PERIOD]

Arguments

  • SYMBOLS - Comma-separated ticker symbols (minimum 2)
  • --period - Historical period: 1mo, 3mo, 6mo, 1y (default: 3mo)

Output

  • symbols - List of symbols analyzed
  • period - Time period used
  • correlation_matrix - Nested dict with correlation values between all pairs

Interpretation

  • Correlation near 1.0 = highly correlated (move together)
  • Correlation near -1.0 = negatively correlated (move opposite)
  • Correlation near 0 = uncorrelated (independent movement)
  • For diversification, prefer low/negative correlations

Examples

# Portfolio correlation
uv run python scripts/correlation.py AAPL,MSFT,GOOGL,AMZN

# Sector comparison
uv run python scripts/correlation.py XLF,XLK,XLE,XLV --period 6mo

# Check hedge effectiveness
uv run python scripts/correlation.py SPY,GLD,TLT

Dependencies

  • numpy
  • pandas
  • pandas-ta
  • yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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