Skillshub generating-trading-signals

install
source · Clone the upstream repo
git clone https://github.com/ComeOnOliver/skillshub
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ComeOnOliver/skillshub "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/jeremylongshore/claude-code-plugins-plus-skills/generating-trading-signals" ~/.claude/skills/comeonoliver-skillshub-generating-trading-signals && rm -rf "$T"
manifest: skills/jeremylongshore/claude-code-plugins-plus-skills/generating-trading-signals/SKILL.md
source content

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

ErrorCauseFix
No data for symbolInvalid ticker or delistedVerify symbol exists on Yahoo Finance
Insufficient dataPeriod too short for indicatorsUse
--period 6m
minimum
Rate limit exceededToo many rapid API callsAdd delay between scans

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