Max daily loss
Halt new trades (and optionally close open ones) when session PnL crosses a set negative threshold, e.g. -3% of starting equity. Stops one bad day from becoming a wipeout.
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AI Trading Bot Risk & Logic Analyzer
Most trading bot failures aren't caused by bad code alone. They come from unclear entry rules, weak exits, oversized positions, missing spread filters, poor stop-loss logic, and strategies that were never tested across different market conditions. This free AI trading bot analyzer helps you break down an automated strategy before you risk real money. Paste MQL5, Pine Script, Python-style bot logic, or plain-English rules and get a structured strategy blueprint, risk breakdown, warning flags, and copy-ready prompts.
Not Financial Advice
This tool is for educational and informational purposes only. It does not provide financial, investment, or trading advice. It does not generate trading signals or recommendations to buy, sell, or hold any asset. Trading involves risk, and automated strategies can lose money. Always backtest, paper trade, and consult a qualified financial professional before risking real capital.
Common Trading Bot Safeguards Worth Considering
A short reference of the safeguards that quietly separate hobby bots from ones that can survive a bad week. Educational only — no code snippets, just the concepts and why they matter.
Once your strategy rules are written clearly, it usually makes sense to chart them before automating them. A charting platform such as TradingView can help you compare entries, exits, indicators, alerts, and market conditions. If the rules are clear enough, a no-code automation platform such as Coinrule may help you explore how rule-based bot workflows are structured.
Max trades per day
Cap the number of entries per session so a signal-heavy day doesn't compound overtrading into overexposure.
Spread filter
Skip new orders when the current spread is above a sane multiple of the average. Session opens and news are the usual culprits.
Slippage limit
Cap allowed deviation on order send so you don't get filled far from the intended price. Any beyond-limit fill is rejected.
Cooldown after loss
Pause new entries for N minutes or M bars after a loss (or a losing streak) to avoid emotional-feeling revenge trades from the bot itself.
Time / session filter
Only trade within defined hours in broker time. Keeps the strategy in the sessions it was designed and tested for.
News filter placeholder
A helper that blocks entries around scheduled high-impact events. Wire it to a real calendar later — the placeholder documents the intent.
Paper trading mode
A config flag that runs the full logic without sending real orders. Non-negotiable before any live deployment.
Detailed trade logging
Every trade gets a human-readable reason, indicator values at entry, spread, slippage, and PnL. Post-hoc review is where bots actually improve.
Equity curve protection
Reduce size or pause entirely when a rolling drawdown exceeds a threshold. Trend-following your own equity curve, defensively.
Want the full strategy report?
A future Pro version could save reports, compare strategy versions, export PDFs, and generate platform-specific code prompts.
No spam. Educational updates only. Not financial advice.
Who this tool is for
Whether you're reviewing an Expert Advisor, checking a Pine Script strategy, or shipping a trading dashboard, the analyzer gives you a shared blueprint to reason from.
MT5 traders
Review an MQL5 Expert Advisor before running it on a live account.
TradingView users
Check a Pine Script strategy for repaint risk, weak exits, and missing filters.
Vibe coders
Building a trading dashboard or bot UI and want a clean spec to work from.
Traders prepping a backtest
Get a checklist of regimes, symbols, and metrics before you run a single test.
Developers converting logic
Moving a strategy between MQL5, Pine Script, and Python without silently changing rules.
Curious learners
New to automated trading and want a plain-English breakdown of how a bot actually works.
What the analyzer checks
The tool works as a structured trading strategy risk calculator and code reviewer, focused on the parts of a bot that quietly break in live markets.
Entry conditions
Exit conditions
Stop-loss logic
Take-profit logic
ATR risk settings
Position sizing
Spread and slippage filters
Session filters
Trailing stops
Backtest readiness
Dangerous assumptions
Prompt quality for AI coding tools
Why this is different from a code summarizer
Most AI tools will happily summarize what a strategy does. That's not enough when real money is on the line. This analyzer turns your MQL5 EA, Pine Script strategy, or plain-English rules into five artifacts you can act on:
- A bot blueprintPlatform, style, indicators, entries, exits, and risk model in plain English.
- A risk reviewSizing, stop type, spread filter, daily loss guard, and max open trades — flagged when missing.
- A warning checklistSeverity-tagged anti-patterns: martingale behavior, missing stops, repaint risk, overfit surface.
- A backtesting planRegimes, symbols, timeframes, and the exact metrics to report before going live.
- A prompt packCopy-ready prompts to improve, convert, harden, or debug the strategy with any AI coding tool.
Example: Bollinger + RSI + ATR bot blueprint
The built-in demo strategy looks for exhaustion outside Bollinger Bands, confirms with RSI extremes, uses ATR to estimate candle size and stop distance, places pending stop orders instead of instant market orders, and manages risk with percent-based lot sizing. This is an educational example — not a claim of profitability.
Long entry
Price closes below the lower Bollinger band, RSI is oversold, and candle size clears an ATR-based threshold. A BuyStop is placed a small ATR fraction above price.
Short entry
Price closes above the upper Bollinger band, RSI is overbought, and candle size clears the ATR threshold. A SellStop is placed a small ATR fraction below price.
Exits
Stop loss at entry ± ATR × 2.0, take profit at the opposite Bollinger band, ATR × 1.5 trailing stop once in profit, and an opposite-signal exit as a fallback.
Filters & sizing
Spread and slippage caps, a broker-time session filter, and percent-of-balance sizing where lots scale to the ATR-based stop distance.
Load this into the tool with to see the full report. Educational use only — no signals, no profit guarantees.
Keep going
Explore VibeCodeCopy for more AI coding tools, trading bot and vibe coding guides, and the vibe coding prompt generator for turning ideas into production-ready prompts.
How to use the trading bot analyzer
Paste your strategy — MQL5 Expert Advisor source, Pine Script, Python bot logic, or a plain-English rule set — into the box above. The analyzer runs entirely in your browser: nothing is uploaded, nothing is stored. It detects common indicators (Bollinger Bands, RSI, ATR, moving averages, MACD, stochastic, ADX, Ichimoku), classifies the strategy style (mean-reversion, breakout, trend-following, scalping, grid), and reconstructs the entries, exits, and risk model in plain English.
Why "risk & logic" and not "profit"
You can't tell whether a trading bot will make money by staring at its code. What you can tell is whether it has a stop loss, whether it guards against catastrophic days, whether it filters spread, whether it repaints, and whether the position sizing survives a losing streak. Those are the questions this tool answers. If a strategy fails that structural review, no amount of parameter optimization will save it in live markets.
What "AI slop" looks like in trading bots
A common pattern in 2026 is asking an AI to "write me a profitable EA." What comes back is usually a 200-line file with a beautiful equity curve on the training window and none of the guardrails that keep it alive on new data: no daily loss cap, no spread filter, no slippage handling, no session filter, and often a stop-loss variable that is defined but never actually attached to the order. This analyzer is designed to catch exactly that class of mistake so you can either fix it or throw the strategy out before it costs you.
Turning the prompt pack into a real workflow
The generated Prompt Pack is designed to move a strategy along a pipeline: explain → audit → harden → convert → backtest plan → developer spec. Copy one prompt at a time into your AI tool of choice, apply the diff, re-run the analyzer, and repeat. If you want a small dashboard to log trades and visualize the results, Lovable is a fast way to spin one up without setting up a full stack.
Frequently asked questions
What is a trading bot risk analyzer?
A trading bot risk analyzer is a tool that reviews the logic of an automated trading strategy — entry rules, exits, stop losses, position sizing, and filters — and highlights weak points before you risk real capital. It doesn't predict profitability. It answers 'what is this bot actually doing, and where can it hurt me?' so you can improve the code and design a serious backtest.
Can this tool tell me if a bot is profitable?
No. Nothing on this page attempts to predict returns, win rate, or drawdown. Profitability is a function of live market conditions, execution, spread, slippage, broker behavior, and — crucially — how you handle losing streaks. This tool only reviews the strategy's structure and calls out risk anti-patterns.
Does this work with MQL5 Expert Advisors?
Yes. Paste the full MQL5 source or just the relevant OnTick / OnInit blocks. The analyzer scans for common signatures — iBands, iRSI, iATR, OrderSend, BuyStop, SellStop, trailing stop, lot sizing off balance/equity/free margin — and reconstructs a plain-English blueprint plus warning flags.
Does this work with TradingView Pine Script?
Yes. Paste Pine v5 or v6 code. The analyzer looks for strategy.entry, strategy.exit, strategy.close, ta.rsi, ta.atr, ta.bbands, and similar built-ins, then explains the entries, exits, and any repainting risk (e.g. referencing the current unfinished bar).
What is ATR-based risk?
ATR (Average True Range) measures recent price volatility. ATR-based risk means the stop loss and sometimes the position size adapt to volatility: a wider stop in a volatile market, tighter in a calm one. Position size is then scaled so the dollar risk stays constant even when the stop distance changes. This is generally more robust than a fixed-pip stop.
Why does spread matter in trading bots?
Spread is a fixed cost on every trade. A bot that looks profitable on a zero-spread backtest can flip to negative expectancy once realistic spread and commission are included, especially on lower timeframes or exotic pairs. Every serious backtest should include spread and commission, and the live bot should refuse to trade when the spread is abnormally wide.
What should I check before running a bot live?
At minimum: multiple market regimes (trend, range, high-volatility), multiple symbols and timeframes, realistic spread and commission, out-of-sample data, max drawdown, average trade, profit factor, and worst losing streak. Then paper trade on a demo account for weeks — not hours — before committing real capital.
Is this financial advice?
No. This tool is for educational and informational purposes only. It does not provide financial, investment, or trading advice. It does not generate trading signals or recommendations to buy, sell, or hold any asset. Trading involves risk, and automated strategies can lose money. Always backtest, paper trade, and consult a qualified financial professional before risking real capital.
Turn messy bot logic into a clear trading strategy blueprint
Paste your MQL5 EA, Pine Script strategy, or plain-English rules and get a risk-first breakdown in seconds.
Educational use only. No trading signals. No profit guarantees.
This tool is for educational and informational purposes only. It does not provide financial, investment, or trading advice. It does not generate trading signals or recommendations to buy, sell, or hold any asset. Trading involves risk, and automated strategies can lose money. Always backtest, paper trade, and consult a qualified financial professional before risking real capital.