What indicators does this skill use?

The skill uses seven indicators: RSI, MACD, Bollinger Bands, Trend (SMA), Volume, Stochastic Oscillator, and ADX.

Can I analyze multiple assets at once?

Yes, you can perform a quick signal scan across multiple assets using the provided scanner script.

How do I filter signals by confidence?

You can filter signals by confidence using command-line options to specify minimum confidence levels.

Is visualization supported?

While visualization is not built-in, you can install matplotlib for optional graphical representation of data.

What should I do if I encounter an error?

Refer to the error handling section in the documentation for guidance on common issues and their fixes.

Generating Trading Signals

Name: Generating Trading Signals
Availability: InStock
Author: jeremylongshore

Free

Get actionable trading signals using technical analysis.

by jeremylongshore2.6k stars on jeremylongshore/claude-code-plugins-plus-skills

1 views

Updated Aug 10, 2026

Get this skill

Free · Opens the source repo

What Generating Trading Signals does

Generating Trading Signals is a Python-based skill designed for traders seeking to enhance their decision-making through technical analysis. By utilizing seven well-known indicators, including RSI, MACD, and Bollinger Bands, this skill generates composite BUY/SELL signals along with confidence scores. This enables users to assess trading opportunities across various assets effectively. The integration of multiple indicators allows for a more nuanced understanding of market conditions, providing traders with a clearer picture of potential entry and exit points.

The skill is straightforward to use, requiring minimal setup. Users can quickly scan multiple assets, such as cryptocurrencies or stocks, to identify trading signals. The output includes not just the signal type but also confidence levels, which helps traders gauge the reliability of each signal. For those looking for deeper insights, the skill offers detailed analyses for specific symbols, breaking down the contributions of each indicator to the overall signal.

This skill is particularly useful for traders who rely on technical analysis as part of their strategy. It can be employed in various market conditions, whether for day trading or longer-term investments. Additionally, the ability to filter and rank signals based on confidence levels aids in prioritizing which opportunities to pursue. The skill also supports exporting results to JSON, making it easy to integrate into automated trading systems or further analysis workflows.

Overall, Generating Trading Signals is a practical tool for both novice and experienced traders who want to leverage technical indicators to inform their trading decisions. With its focus on clarity and actionable insights, it serves as a valuable addition to any trader's toolkit.

When to use it

Use this skill when you need to analyze assets for trading opportunities based on technical indicators.

When not to use it

This skill may not be suitable for traders who prefer fundamental analysis or those looking for automated trading without manual input.

What you can build with it

Quick Market Scan

Perform a rapid analysis of the top 10 cryptocurrencies to identify potential trading opportunities.

In-Depth Symbol Analysis

Get a detailed breakdown of indicators for a specific asset, like Bitcoin, to understand its trading signals.

Exporting Trading Signals

Save filtered trading signals to a JSON file for integration into automated trading systems or further analysis.

How to install Generating Trading Signals

View source

1. Install with the skills CLI

npx skills add jeremylongshore/claude-code-plugins-plus-skills/generating-trading-signals --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by jeremylongshore

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

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.
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.

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

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

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 ${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

Frequently asked questions about Generating Trading Signals

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