Crypto Trader & Analyst Skill

This skill allows OpenClaw to analyze the crypto market using technical indicators and news sentiment, record its findings, and execute trades on Binance.

Dependencies

Ensure the following Python packages are installed:

pip install ccxt pandas pandas-ta requests TextBlob

Note: TextBlob is suggested for basic sentiment analysis if needed, though simple keyword matching might suffice.

Environment Variables

You must set the following environment variables for trading:

• BINANCE_API_KEY: Your Binance API Key.
• BINANCE_API_SECRET: Your Binance API Secret.

WARNING: Never share these keys or commit them to version control.

Workflow

1. Market Analysis

Technical Analysis Run the market data script to get current indicators for a symbol (default ETH/USDT).

python skills/crypto_trader/scripts/market_data.py --symbol ETH/USDT

Output: JSON containing RSI, MACD, close price, etc.

Sentiment Analysis Run the sentiment script to fetch latest news headers and forum buzz.

python skills/crypto_trader/scripts/sentiment_data.py

Output: Text/JSON summary of positive/negative news.

2. Decision Making & Logging

Analyze & Record Based on the outputs from step 1, form a hypothesis. Is the market Bullish, Bearish, or Neutral? Before trading, you MUST save your analysis.

python skills/crypto_trader/scripts/logger.py "Your detailed analysis here. E.g., RSI is 30 (oversold) and news is positive. Planning to BUY."

3. Execution

Trade If the analysis supports a trade, execute it.

# Buy 0.01 ETH at Market Price
python skills/crypto_trader/scripts/trade.py --symbol ETH/USDT --side buy --amount 0.01 --type market

# Dry Run (Test without real money)
python skills/crypto_trader/scripts/trade.py --symbol ETH/USDT --side buy --amount 0.01 --dry-run

The trade script will automatically append the transaction to skills/crypto_trader/logs/trade_history.csv.

Files structure

• scripts/market_data.py: Fetches OHLCV and calculates indicators.
• scripts/sentiment_data.py: Fetches news/forum data.
• scripts/logger.py: Appends analysis to logs/analysis_journal.md.
• scripts/trade.py: Executes trades and logs to logs/trade_history.csv.
• logs/: Directory storing your analysis history and trade logs.