--- name: generating-trading-signals-1b19c85efa04 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: 1.31.0 author: Jeremy Longshore 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: ```bash set -euo pipefail pip install yfinance pandas numpy ``` Optional for visualization: `pip install matplotlib` ## Instructions 1. **Quick signal scan** across multiple assets: ```bash 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: ```bash 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: ```bash # 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**: ```bash 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 [`references/implementation.md`](references/implementation.md) for full output format examples and signal type tables. ## Error Handling | Error | Cause | Fix | |-------|-------|-----| | No data for symbol | Invalid ticker or delisted | Verify symbol exists on Yahoo Finance | | Insufficient data | Period too short for indicators | Use `--period 6m` minimum | | Rate limit exceeded | Too many rapid API calls | Add delay between scans | See [`references/errors.md`](references/errors.md) for comprehensive error handling. ## Examples **Morning crypto scan** - Check all top-10 crypto assets for entry opportunities: ```bash python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --watchlist crypto_top10 --period 6m ``` **Deep dive on Bitcoin** - Full indicator breakdown with risk management levels: ```bash python ${CLAUDE_SKILL_DIR}/scripts/scanner.py --symbols BTC-USD --detail ``` **Find strongest DeFi buy signals** - Filter and rank by confidence: ```bash 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: ```bash 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 - [`references/implementation.md`](references/implementation.md) - Output formats, configuration, backtester integration, file reference --- Source attribution: jeremylongshore Original project: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/ab85a061f7bcc039dac13ee193de7a4cd4388571/plugins/crypto/crypto-signal-generator/skills/generating-trading-signals/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2024-2026 Jeremy Longshore & Contributors Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: jeremylongshore Original project: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/ab85a061f7bcc039dac13ee193de7a4cd4388571/plugins/crypto/crypto-signal-generator/skills/generating-trading-signals/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Finance & Accounting, Marketing Roles: Data Analyst, Financial Analyst, Growth Marketer, Marketing Analyst, Product Marketer Specialties: API, Backend, Design, Frontend, Testing Tools: Matplotlib, Numpy, Pandas, Yfinance Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 69b5458852024e515435c6699ccb1dbb836abb54f85193710731d33eaadc96a0