Imported from jeremylongshore/tons-of-skills-marketplace (skills/.curated/generating-trading-signals/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill generating-trading-signals. Copyright stays with the author (MIT).

Generating Trading Signals

Overview

Multi-indicator signal generation system that analyzes price action using 7 technical indicators and produces composite BUY/SELL signals with confidence scores and risk management levels.

Indicators: RSI, MACD, Bollinger Bands, Trend (SMA 20/50/200), Volume, Stochastic Oscillator, ADX.

Prerequisites

Install required dependencies:

set -euo pipefail
pip install yfinance pandas numpy

Optional for visualization: pip install matplotlib

Instructions

1. Quick signal scan across multiple assets:

   python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --watchlist crypto_top10 --period 6m

   Output shows signal type (STRONG_BUY/BUY/NEUTRAL/SELL/STRONG_SELL) and confidence per asset.

2. Detailed signal analysis for a specific symbol:

   python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --symbols BTC-USD --detail

   Shows each indicator's individual signal, value, and reasoning.

3. Filter and rank the best opportunities:

   # Only buy signals with 70%+ confidence
   python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --filter buy --min-confidence 70 --rank confidence
   
   # Save results to JSON
   python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --output signals.json

4. Use predefined watchlists:

   python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --list-watchlists
   python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --watchlist crypto_defi

   Available: crypto_top10, crypto_defi, crypto_layer2, stocks_tech, etfs_major

Output

The scanner produces a summary table with symbol, signal type, confidence %, price, and stop loss for each asset scanned. Detailed mode adds per-indicator breakdowns with risk management levels (stop loss, take profit, risk/reward ratio).

Signal types: STRONG_BUY (+2), BUY (+1), NEUTRAL (0), SELL (-1), STRONG_SELL (-2)

Confidence ranges: 70-100% high conviction | 50-70% moderate | 30-50% weak | 0-30% avoid

See ${CLAUDE_SKILL_DIR}/references/implementation.md for full output format examples and signal type tables.

Error Handling

See ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error handling.

Examples

Morning crypto scan - Check all top-10 crypto assets for entry opportunities:

python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --watchlist crypto_top10 --period 6m

Deep dive on Bitcoin - Full indicator breakdown with risk management levels:

python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --symbols BTC-USD --detail

Find strongest DeFi buy signals - Filter and rank by confidence:

python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --watchlist crypto_defi --filter buy --rank confidence

Export results - Save to JSON for automated pipeline or further analysis:

python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --watchlist crypto_top10 --output signals.json

Resources

• yfinance for price data
• pandas/numpy for calculations
• Compatible with trading-strategy-backtester plugin
• ${CLAUDE_SKILL_DIR}/references/implementation.md - Output formats, configuration, backtester integration, file reference