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数据与研究 · SKILL.md

generating-trading-signals

generating-trading-signals

【数据与研究】Generate trading signals using technical indicators (RSI, MACD, Bollinger Bands, etc.). Combines multiple indicators into composite signals with confidence scores. Use when analyzing assets for trading opportunities or checking technical indicators. Trigger with phrases like "get trading signals", "check indicators", "analyze for entry", "scan for op…

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技能说明

GitHub

name: generating-trading-signals description: 'Generate trading signals using technical indicators (RSI, MACD, Bollinger Bands, etc.).

Combines multiple indicators into composite signals with confidence scores.

Use when analyzing assets for trading opportunities or checking technical indicators.

Trigger with phrases like "get trading signals", "check indicators", "analyze for entry",

"scan for opportunities", "generate buy/sell signals", or "technical analysis".

' allowed-tools: Read, Write, Edit, Grep, Glob, Bash(python:*) version: 1.30.0 author: Jeremy Longshore jeremy@intentsolutions.io license: MIT tags:

  • crypto
  • trading-signals compatibility: Designed for Claude Code

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
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