Turn research notes into automated execution with Coinrule. Draft AI-assisted rules, test them, then deploy across major exchanges with non-custodial controls.
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Instead of copying signals by hand, an LLM trading agent workflow can start with your thesis and end with consistent orders. In Coinrule, you translate intent into clear if-this-then-that logic, then run it on Binance, Kraken or Hyperliquid with defined risk limits.
Traders often confuse clever analysis with tradable rules. This platform forces precision: entries, exits, position sizing and cooldowns are explicit. You can cap exposure per asset, set max daily loss and require confirmations like volume or trend filters before any order fires.
Before deploying, validate ideas with historical checks and paper-style iteration. Compare variants by changing one variable at a time, like RSI 30 vs 35, or 1H vs 4H candles. Once results look stable, switch to live execution and monitor logs for every decision.
Prompt To Rule Translation
Write a simple intent like: buy when momentum returns after a pullback. Then formalize it: if price is above MA200 and RSI(1H) crosses above 40 after being below 35, buy 2 percent of balance. Add an exit: take profit at 6 percent or trail 2.5 percent once profit exceeds 3 percent.
Non-Custodial By Design
Your funds stay on the venue. Coinrule connects via API keys for centralized exchanges, or via smart accounts for on-chain execution, so you keep control while the system automates the routine work.
Volatility Breakout
Buys when price breaks above the prior 24H high with rising volume. Sets a 2.5% stop loss and takes profit at 5%. Works best on 1H to 4H charts.
RSI Oversold Rebound
Enters when RSI drops below 30 on 4H candles and then crosses back above 32. Exits when RSI exceeds 60 or after a time stop of 3 days. Adds a 3% protective stop.
Grid Trading
Places a grid of buys and sells inside a defined range, like plus or minus 6% around a midpoint. Rebalances orders as fills occur. Uses a max position cap to avoid overexposure.
Stop Loss and Trailing Take Profit
Opens on a trend confirmation, then protects downside with a fixed stop like 2%. Switches to a trailing take profit of 1.8% once price is up 3%. Designed to cut losers fast and ride winners.
MA Crossover with Volume Filter
Buys when MA20 crosses above MA50 and volume is above its 20-period average. Sells on the reverse cross or a 4% stop. Useful for avoiding low-liquidity whipsaws.
Volatility Breakout
Buys when price breaks above the prior 24H high with rising volume. Sets a 2.5% stop loss and takes profit at 5%. Works best on 1H to 4H charts.
RSI Oversold Rebound
Enters when RSI drops below 30 on 4H candles and then crosses back above 32. Exits when RSI exceeds 60 or after a time stop of 3 days. Adds a 3% protective stop.
Grid Trading
Places a grid of buys and sells inside a defined range, like plus or minus 6% around a midpoint. Rebalances orders as fills occur. Uses a max position cap to avoid overexposure.
Stop Loss and Trailing Take Profit
Opens on a trend confirmation, then protects downside with a fixed stop like 2%. Switches to a trailing take profit of 1.8% once price is up 3%. Designed to cut losers fast and ride winners.
MA Crossover with Volume Filter
Buys when MA20 crosses above MA50 and volume is above its 20-period average. Sells on the reverse cross or a 4% stop. Useful for avoiding low-liquidity whipsaws.
Bollinger Band Mean Reversion
Buys when price closes below the lower band and RSI is under 40 on 1H candles. Sells at the middle band or after 12 hours. Adds a tight stop to limit tail risk.
Funding Rate Hedge
When funding turns strongly positive, reduces long exposure and adds a hedge. When funding normalizes, removes the hedge. Built for perps environments where carry can dominate returns.
Portfolio Rebalance
Rebalances back to target weights weekly, like 50% BTC, 30% ETH, 20% SOL. Skips trades if drift is under 2% to reduce fees. Helps maintain risk discipline through cycles.
Dynamic Grid with ATR Spacing
Builds grid levels using ATR so spacing widens during high volatility and tightens in calm markets. Adds a hard max drawdown rule to pause the grid. Designed for range phases that shift over time.
Perps Trend Follower
Enters when price is above MA200 and ADX confirms trend strength above 20. Exits on a close below MA50 or a trailing stop. Best on 4H to daily timeframes for fewer false signals.
Unlike a black-box model, rules stay auditable. Use AI to draft hypotheses, name variables and propose filters, then lock the final logic into deterministic conditions. That way you can answer why a trade happened, not just that it happened.
Start with a single market and one timeframe. Define a trigger, a confirmation and a risk response. For example: if BTC drops 5% in 4 hours and RSI(1H) is below 35, buy 1% of balance, then set a 2% stop and a 4% take profit. Add a cooldown of 6 hours to prevent rapid re-entry. Only after it behaves should you expand to more pairs.
For crypto automation, Coinrule can run the same playbook across Coinbase, Bybit, KuCoin and OKX. You can separate rules by venue, or keep one strategy and adjust sizing per exchange. Logs and alerts keep you informed when conditions trigger and orders fill.
When you prefer decentralized execution, use smart accounts with session keys for limited permissions. Trades route via Li.fi to find efficient liquidity across supported networks. You keep a clear boundary between strategy logic and custody.
Launch BotFAQ
Sofia G.
Diego R.
Hiroshi Y.
Amara N.
James W.
Priya K.
Markets punish brittle logic. Build with ranges, not single points, and assume slippage, gaps and sudden volatility. Use time stops, partial exits and position caps so one bad regime does not dominate outcomes.
Treat AI output as a draft, not a decision. Convert each claim into a measurable signal, then decide what invalidates it. If you cannot define an exit, the idea is not ready for automation.
Templates give you a known starting point for common patterns like breakouts, mean reversion and rebalancing. Clone one, change a single parameter and retest. This keeps iteration disciplined and comparable.
Set alerts for fills, drawdowns and rule pauses so you do not babysit charts. Review decision logs weekly to spot false triggers and missed exits. Small tweaks beat constant rewrites.
Increase size gradually and expand to more pairs only when behavior stays consistent across different weeks. Diversify triggers so one indicator does not control everything. Keep a manual override for unusual events.
Pick a template, set your thresholds and connect an exchange. Run with small size, review results and iterate. When you are ready, deploy the same logic across venues with consistent risk settings.
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