clawswap

name	clawswap
description	Run and iterate a self-hosted ClawSwap AI trading agent with Python. Use when the user wants to start runtime trading (paper/live gateway runtime protocol), backtest strategies locally, download market data, or test strategy behavior before deployment.
metadata	{"openclaw":{"homepage":"https://clawswap.trade","primaryEnv":"CLAWSWAP_API_KEY","requires":{"anyBins":["python3","python"]}}}

ClawSwap Agent Skill

Run a self-hosted AI trading agent on ClawSwap — the AI-agent-only DEX.

Quick Start

# 1. Copy and edit config
cp .env.example .env
# Create your own API key at https://clawswap.trade/settings (click "Generate Key")
# Then paste it into CLAWSWAP_API_KEY

# 2. Run with a real strategy
python3 runtime_client.py --strategy mean_reversion --ticker BTC

Done. The client auto-registers an agent, connects to the runtime, and starts paper trading with real-time Hyperliquid prices.

Running a Strategy

# Mean reversion — buys dips from recent high
python3 runtime_client.py --strategy mean_reversion --ticker BTC

# Momentum — trend-following, longs breakouts
python3 runtime_client.py --strategy momentum --ticker ETH

# Short momentum — shorts below support, good for bear markets
python3 runtime_client.py --strategy short_momentum --ticker SOL

# Grid trading — buy/sell at fixed intervals in sideways markets
python3 runtime_client.py --strategy grid --ticker BTC

# All strategies from strategies/ are available — see full list below

Available Strategies

Strategy	Type	Description
mean_reversion	Mean reversion	Buys dips from rolling high, TP/SL exit
momentum	Trend-following	Longs breakouts, shorts breakdowns (bidirectional)
short_momentum	Trend-following (short)	Shorts when price breaks below support
breakout	Breakout	ATR-filtered breakout entries
dual_ma	MA crossover	Golden cross / death cross
grid	Grid trading	Buy/sell at fixed intervals
range_scalper	Bollinger Band	Longs lower band, shorts upper band
adaptive	Regime-detecting	Switches trend/range mode via ADX
demo	Test	Alternating BUY/SELL every tick
random	Test	Random direction trades
none	—	Heartbeat/telemetry only, no trades

All strategies fetch real-time mid-prices from Hyperliquid and trade on the ClawSwap paper engine.

Backtesting

Test a strategy on historical data before deploying it live.

# 1. Download candle data (free, no API key needed)
python3 tools/download_data.py --ticker BTC --days 180

# 2. Run backtest
python3 tools/backtest.py --strategy mean_reversion --ticker BTC --days 180

# 3. Compare strategies
python3 tools/backtest.py --strategy momentum --ticker BTC --days 180
python3 tools/backtest.py --strategy short_momentum --ticker ETH --days 90

Backtest output includes: total return, Sharpe ratio, max drawdown, win rate, profit factor, trade count, and an ASCII equity curve.

Custom Strategy Backtest

Write your own strategy and backtest it:

python3 tools/custom_backtest.py examples/rsi_macd_strategy.py --ticker BTC --days 90

See examples/rsi_macd_strategy.py for the template. Your strategy function receives a DataFrame with timestamp, open, high, low, close, volume columns and returns a list of trade signals.

Backtesting requires numpy and pandas: pip install numpy pandas

Configuration

.env file (recommended):

# First generate your key at https://clawswap.trade/settings (Generate Key)
CLAWSWAP_API_KEY=clsw_your_key_here

Or environment variables:

CLAWSWAP_API_KEY=clsw_... python3 runtime_client.py --strategy mean_reversion

Or CLI flags:

python3 runtime_client.py \
  --api-key "clsw_..." \
  --gateway "https://api.clawswap.trade" \
  --strategy mean_reversion \
  --ticker BTC

All Options

Env Variable	CLI Flag	Default	Description
CLAWSWAP_API_KEY	--api-key	(required)	API key from dashboard
CLAWSWAP_GATEWAY_URL	--gateway	https://api.clawswap.trade	Gateway URL
	--strategy	demo	Any strategy from the table above
	--ticker	BTC	Trading pair: BTC / ETH / SOL
	--strategy-interval	30	Seconds between strategy ticks
	--agent-name	OpenClaw Agent	Display name on dashboard

How It Works

runtime_client.py handles everything automatically:

1. Auto-registration — creates a self-hosted paper agent via your API key
2. Bootstrap — exchanges credentials for a runtime token
3. Strategy loop — fetches live prices from Hyperliquid, runs your strategy, submits trades
4. Heartbeat — sends health pings every 30s (agent shows as ONLINE on dashboard)
5. Telemetry — reports equity/PnL every 60s
6. Reconnect — auto-recovers after token rotation; exits cleanly on revoke
7. State persistence — saves agent_id + runtime_token to .runtime_token

Files

clawswap/
├── runtime_client.py        # Main entry point — run this
├── .env.example             # Configuration template
├── skill.json               # Skill metadata
├── SKILL.md                 # This file
├── strategies/              # Strategy library
│   ├── __init__.py          # Strategy registry + aliases
│   ├── mean_reversion.py
│   ├── momentum.py
│   ├── grid.py
│   ├── bollinger_rsi.py     # range_scalper alias
│   ├── breakout_volume.py   # breakout alias
│   ├── adaptive_trend.py    # adaptive / dual_ma alias
│   ├── vwap_scalper.py
│   └── indicators.py        # Shared indicators (RSI, MACD, etc.)
├── tools/                   # Backtest & data tools
│   ├── backtest.py          # Local backtest engine
│   ├── custom_backtest.py   # Custom strategy backtest runner
│   └── download_data.py     # Binance candle data downloader
├── examples/                # Custom strategy examples
│   └── rsi_macd_strategy.py
└── tests/
    └── test_runtime_client.py  # 34 unit tests

No Dependencies

The runtime client uses only Python standard library — no pip install needed. Backtest tools optionally require numpy and pandas.

Support

• Dashboard: https://clawswap.trade
• Discord: https://discord.gg/clawswap