Technical Analysis
Computes technical indicators for stock data including MACD, RSI, moving averages, Bollinger Bands, ATR, and volume analysis. Generates trading signals based on indicator conditions. Trigger when the user requests technical indicators, chart patterns, or signal calculations.
Install
$ agentstack add skill-qunyou-agent-finance-skills-technical-analysis ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
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Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-qunyou-agent-finance-skills-technical-analysis) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
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Technical Analysis
Computes and interprets technical indicators for financial time series data.
Real Code Reference
tradinglearn/utils/technical_indicators.py—calculate_macd(),calculate_ema(),calculate_sma()tradinglearn/strategies/macd_strategy.py—MACDStrategy.generate_signals()with golden-cross/dead-cross logictradinglearn/pytdx2/macd_golden_cross.py— A-share MACD golden cross scanner
Supported Indicators
- Trend: SMA, EMA, WMA, MACD, Parabolic SAR, ADX
- Momentum: RSI, Stochastic Oscillator, Williams %R, ROC, CCI
- Volatility: Bollinger Bands, ATR, Keltner Channels
- Volume: OBV, Volume Profile, Money Flow Index, VWAP
- Patterns: Doji, Hammer, Engulfing, Morning/Evening Star
Typical Workflow
- Fetch K-line data via
fetch_stock_data(ticker)orQuotationClient.get_KLine_data() - Compute indicators with existing functions in
utils/technical_indicators.py - Generate signals: crossover events, overbought/oversold thresholds, divergence detection
- Return DataFrame with indicator columns + signal columns
Usage
from utils.technical_indicators import calculate_macd, calculate_ema, calculate_sma
macd_df = calculate_macd(data, fast_period=12, slow_period=26, signal_period=9)
# Returns DataFrame with MACD, Signal, Histogram columns
signal = macd_df['MACD'] > macd_df['Signal'] # Golden cross conditionSource & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: qunyou-agent
- Source: qunyou-agent/finance-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.