What are the prerequisites?

A Binance account with spot API keys (withdrawals disabled), an Anthropic Haiku API key (LLM), and Python 3.10+.

Which strategies are supported?

Momentum, Mean Reversion, and DCA, plus an LLM-Enhanced mode that consults sentiment before trades.

How do I manage risk and limits?

Configure TRADE_SIZE_PCT, TAKE_PROFIT_PCT, STOP_LOSS_PCT, MAX_POSITIONS, and DCA_INTERVAL; start small and paper trade first.

Binance Spot Trader

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@srikanthbellary

npx machina-cli add skill @srikanthbellary/binance-spot-trader --openclaw

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Binance Spot Trader

Autonomous spot trading bot for Binance. Combines technical indicators with LLM-powered market sentiment analysis to execute trades on any Binance spot pair.

Prerequisites

Binance account with API keys (spot trading enabled, withdrawal DISABLED)
Anthropic API key (uses Haiku ~$0.001/eval)
Python 3.10+

Setup

1. Install

bash {baseDir}/scripts/setup.sh

2. Configure

Create .env:

BINANCE_API_KEY=<your-api-key>
BINANCE_SECRET_KEY=<your-secret-key>
LLM_API_KEY=<anthropic-api-key>
PAIRS=BTCUSDT,ETHUSDT,SOLUSDT
STRATEGY=momentum
TRADE_SIZE_PCT=5
MAX_POSITIONS=5

3. Run

python3 {baseDir}/scripts/trader.py

Or via cron:

*/5 * * * * cd /opt/trader && python3 trader.py >> trader.log 2>&1

Strategies

Momentum (default)

Buys when price crosses above 20-EMA with volume spike
Sells when price crosses below 20-EMA or hits TP/SL
Best for trending markets (BTC, ETH, SOL)

Mean Reversion

Buys when RSI < 30 (oversold) and price near Bollinger Band lower
Sells when RSI > 70 (overbought) or price near upper band
Best for range-bound markets

DCA (Dollar Cost Average)

Buys fixed amount at regular intervals regardless of price
Configurable interval (hourly, daily, weekly)
Lowest risk strategy for long-term accumulation

LLM-Enhanced (all strategies)

Before each trade, asks Claude Haiku for market sentiment
Evaluates: recent news, price action, volume patterns, market structure
Can veto a trade signal if sentiment is strongly against

Trading Parameters

Parameter	Default	Description
`PAIRS`	`BTCUSDT`	Comma-separated trading pairs
`STRATEGY`	`momentum`	`momentum`, `mean_reversion`, or `dca`
`TRADE_SIZE_PCT`	`5`	% of portfolio per trade
`MAX_POSITIONS`	`5`	Max concurrent open positions
`TAKE_PROFIT_PCT`	`5`	Take profit %
`STOP_LOSS_PCT`	`3`	Stop loss %
`DCA_INTERVAL`	`daily`	For DCA: `hourly`, `daily`, `weekly`
`DCA_AMOUNT_USDT`	`50`	USDT per DCA buy
`USE_LLM`	`true`	Enable LLM sentiment filter

Monitoring

# Check portfolio
python3 {baseDir}/scripts/portfolio.py

# View trade history
tail -50 trades.jsonl

# Check logs
tail -f trader.log

⚠️ Security Considerations

NEVER enable withdrawal on API keys — trading only
IP-restrict your API keys on Binance
Use a sub-account with limited funds for bot trading
Start with tiny amounts ($50-100) and paper trade first
Monitor actively during first 24 hours
Set up Binance email alerts for all trades
API keys on disk — secure your server (SSH keys only, firewall, chmod 600)

References

See references/binance-api.md for REST API docs
See references/indicators.md for technical analysis details

Source

git clone https://clawhub.ai/srikanthbellary/binance-spot-traderView on GitHub

Overview

Autonomous Binance spot trading bot that combines technical indicators with LLM-powered market sentiment analysis to execute momentum, mean reversion, and DCA strategies on any spot pair. It supports position sizing and portfolio tracking, enabling automated crypto trading with built-in risk controls.

How This Skill Works

The bot authenticates with Binance via API keys and runs a Python trader that pulls live market data, applies indicators (e.g., 20-EMA, RSI, Bollinger Bands), and consults Anthropic Haiku for sentiment before trading. It enforces risk settings like TAKE_PROFIT_PCT and STOP_LOSS_PCT, sizes positions using TRADE_SIZE_PCT, and tracks active positions across configured PAIRS for automated execution.

When to Use It

You want to automate crypto trading on Binance spot without manual intervention
You want to deploy momentum, mean reversion, or DCA strategies on spot pairs
You want LLM-enhanced sentiment evaluation to vet signals before trading
You manage multiple pairs and need controlled risk with MAX_POSITIONS
You want built-in monitoring of portfolio and trade history

Quick Start

Step 1: Install the bot by running the setup script: bash {baseDir}/scripts/setup.sh
Step 2: Configure: create .env and set BINANCE_API_KEY, BINANCE_SECRET_KEY, LLM_API_KEY, PAIRS, STRATEGY, TRADE_SIZE_PCT, MAX_POSITIONS, etc.
Step 3: Run: python3 {baseDir}/scripts/trader.py or set up a cron job to run it periodically

Best Practices

Start with a small allocation (e.g., $50-100) and use paper trading first
Never enable withdrawals on API keys; IP-restrict keys and use a sub-account
Keep a dedicated environment for the bot and rotate keys regularly
Backtest where possible and monitor performance; review logs daily
Regularly tune STRATEGY, PAIRS, and risk parameters (TRADE_SIZE_PCT, TAKE_PROFIT_PCT, STOP_LOSS_PCT)

Example Use Cases

BTCUSDT momentum trading that uses 5% of the portfolio per trade to capture trends
ETHUSDT and SOLUSDT mean reversion during range-bound periods
DCA purchases on BTCUSDT occurring at a daily interval for long-term accumulation
LLM sentiment veto prevents trades during negative news or unfavorable sentiment
Portfolio-wide monitoring and trade history via built-in portfolio.py and logs

Frequently Asked Questions

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