How do I install the Crypto Trading Strategist skill?

Run npx skillmds@latest add luokai0/crypto-trading-strategist in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Crypto Trading Strategist safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Crypto Trading Strategist?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Crypto Trading Strategist free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Crypto Trading Strategist?

luokai0 (@luokai0) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Crypto Trading Strategist by luokai0

Name: Crypto Trading Strategist
Rating: 4.5 (4 reviews)
Author: luokai0

Crypto Trading Strategist

Provides trading strategies for cryptocurrencies based on Binance market data, calculated technical analysis indicators, and aggregated market sentiment from crypto RSS news feeds. Use when users ask for trading advice, strategy recommendations, or analysis combining price data, TA, and sentiment for crypto assets like ETH, BTC, or altcoins.

luokai0 Updated Sep 9, 2026 10 repo stars

File contents

Trading Strategies Skill

This skill generates data-driven trading strategies for cryptocurrencies by integrating multiple data sources and analytical tools.

Core Components

Binance Market Data: Real-time price, volume, and historical klines from Binance API
Technical Analysis (TA): Calculated indicators including SMA, RSI, MACD, Bollinger Bands, Stochastic, and more
Market Sentiment: Aggregated sentiment scores from popular crypto RSS feeds

Workflow

Step 1: Data Collection

Fetch current ticker data from Binance API (/api/v3/ticker/price and /api/v3/ticker/24hr)
Retrieve historical klines (/api/v3/klines with 30-100 days of data)
Aggregate sentiment using the market-sentiment skill

Step 2: TA Calculation

Use the scripts/calculate_ta.py script to compute indicators from historical data.

Step 3: Strategy Generation

Combine TA signals, price action, and sentiment score to recommend:

Buy/Sell/Hold signals
Entry/exit points
Risk management (stop-loss, position sizing)
Timeframes (swing, day trading)

Usage Examples

Basic Strategy Request

For ETH, generate a trading strategy based on current market data.

→ Fetch ETH data, calculate TA, get sentiment, output strategy.

Advanced Analysis

Analyze BTC with 50-day history, include sentiment, recommend swing trade.

→ Use longer history, focus on swing signals.

Risk Management

Always include stop-loss recommendations
Suggest position sizes (1-5% of capital)
Warn about volatility and leverage risks
Note: Not financial advice

References

TA formulas: See references/ta_formulas.md
Sentiment interpretation: See references/sentiment_guide.md

Scripts

scripts/calculate_ta.py: Python script for TA indicator calculations
scripts/fetch_binance.py: Helper for Binance API calls

./skills/trading-strategies/SKILL.md

---name: crypto-trading-strategistdescription: Provides trading strategies for cryptocurrencies based on Binance market data, calculated technical analysis indicators, and aggregated market sentiment from crypto RSS news feeds. Use when users ask for trading advice, strategy recommendations, or analysis combining price data, TA, and sentiment for crypto assets like ETH, BTC, or altcoins.--- # Trading Strategies Skill This skill generates data-driven trading strategies for cryptocurrencies by integrating multiple data sources and analytical tools. ## Core Components 1. **Binance Market Data**: Real-time price, volume, and historical klines from Binance API 2. **Technical Analysis (TA)**: Calculated indicators including SMA, RSI, MACD, Bollinger Bands, Stochastic, and more 3. **Market Sentiment**: Aggregated sentiment scores from popular crypto RSS feeds ## Workflow ### Step 1: Data Collection - Fetch current ticker data from Binance API (`/api/v3/ticker/price` and `/api/v3/ticker/24hr`) - Retrieve historical klines (`/api/v3/klines` with 30-100 days of data) - Aggregate sentiment using the market-sentiment skill ### Step 2: TA Calculation Use the `scripts/calculate_ta.py` script to compute indicators from historical data. ### Step 3: Strategy Generation Combine TA signals, price action, and sentiment score to recommend: - Buy/Sell/Hold signals - Entry/exit points - Risk management (stop-loss, position sizing) - Timeframes (swing, day trading) ## Usage Examples ### Basic Strategy Request ``` For ETH, generate a trading strategy based on current market data. ``` → Fetch ETH data, calculate TA, get sentiment, output strategy. ### Advanced Analysis ``` Analyze BTC with 50-day history, include sentiment, recommend swing trade. ``` → Use longer history, focus on swing signals. ## Risk Management - Always include stop-loss recommendations - Suggest position sizes (1-5% of capital) - Warn about volatility and leverage risks - Note: Not financial advice ## References - TA formulas: See [references/ta_formulas.md](references/ta_formulas.md) - Sentiment interpretation: See [references/sentiment_guide.md](references/sentiment_guide.md) ## Scripts - `scripts/calculate_ta.py`: Python script for TA indicator calculations - `scripts/fetch_binance.py`: Helper for Binance API calls</content> <parameter name="filePath">./skills/trading-strategies/SKILL.md

Frequently asked questions