AI Prompt Library for FTMO Traders

FTMO’s evaluation framework rejects roughly 90% of applicants — not because traders lack edge, but because they break rules under pressure. The 10% daily drawdown limit and 5% maximum loss threshold are mechanical constraints, yet most failures are behavioral. That gap is exactly where AI-assisted workflows deliver measurable value.

Passing an FTMO challenge isn’t about finding a holy grail setup. It’s about executing a defined process with consistency across 30+ trading days while managing position sizing, news exposure, and emotional decision points. One impulsive trade after three losing days ends the evaluation. AI prompts don’t remove that pressure — they give you a structured response to it.

This library is built specifically for FTMO challenge and verification traders. Every prompt maps to a real constraint inside the FTMO ruleset: daily loss limits, profit targets, trading day minimums, and the psychological weight of funded account performance. Use these prompts with ChatGPT-4o, Claude 3.5, or any capable LLM to build a repeatable, rule-compliant trading process.

Pre-Session Risk Brief: Know Your Numbers Before You Chart

FTMO accounts have hard daily loss limits that vary by account size — $500 on a $10,000 account, $1,000 on $20,000. Before opening a single chart, you need to know your available daily drawdown, current equity relative to the maximum loss threshold, and how many trading days remain in your evaluation window. Most traders do this calculation loosely in their head. That’s how breaches happen.

A pre-session AI brief forces precision. Feed your current equity, account size, open P&L, and days remaining into a prompt and get a structured risk summary back. This takes 90 seconds and eliminates the mental arithmetic errors that compound when you’re already biased from yesterday’s performance.

Run this prompt every single session, not just when you’re down. Knowing you have $800 of daily drawdown available on a day when your bias is strong is equally important as knowing you only have $120 left after a bad open.

You are a prop trading risk manager. I am trading an FTMO $25,000 account.
Current equity: $25,340. Maximum loss threshold: $23,750. Daily loss limit: $1,250.
Today's open P&L: -$180. Trading days completed: 8 of minimum 10.
Profit target: $2,500. Current profit: $340.
Give me a structured pre-session brief: remaining daily drawdown, distance from max loss, daily profit needed to stay on pace, and one risk priority for today's session.

Trade Plan Validation Against FTMO Rules

Most traders write a trade plan and execute it. FTMO traders need one additional step: validating that plan against the specific ruleset they’re operating under. A valid technical setup can still be the wrong trade if it exposes you to a high-impact news event, runs your position size above what your remaining drawdown permits, or occurs on the final day of an evaluation when protecting capital is the dominant priority.

AI is exceptionally useful here as a rules compliance layer. Before executing a trade, paste your plan into a prompt and have the model flag any FTMO-rule conflicts. This is not about getting trade signals from AI — it’s about using AI as a checklist enforcer that doesn’t get caught up in the excitement of a good setup.

This discipline compounds. After 10 evaluations, traders who run plan validation prompts have a documented record of every trade reviewed against the rules. That log becomes a feedback loop for identifying which setup types consistently create rule violations.

You are an FTMO compliance reviewer. Review this trade plan against standard FTMO rules.
Trade: Long EURUSD at 1.0845, stop at 1.0810, target 1.0910. Position size: 0.8 lots.
Account: $10,000 FTMO challenge. Current daily P&L: -$200. Daily loss limit: $500.
Max loss threshold: $9,500. Current equity: $9,780. Days remaining in challenge: 4.
Flag any rule conflicts, calculate maximum position size given remaining daily drawdown,
and note whether this trade should be sized down or skipped entirely.

Drawdown Recovery Protocol: Structured Response to Losing Streaks

Three consecutive losing days on an FTMO account triggers a specific psychological state that kills more evaluations than any technical failure. The response pattern is predictable: traders widen stops, increase size to recover losses faster, or abandon their strategy entirely for something that ’worked last week.’ Every one of those responses accelerates account breach.

A drawdown recovery protocol prompt restructures your thinking around the actual numbers. Instead of operating on emotion, you operate on a calculated plan: reduced position size until equity recovers X%, specific setup filter tightened to highest-probability patterns only, and a defined equity level at which normal sizing resumes. AI generates this plan in seconds from your current equity inputs.

The output isn’t just a plan — it’s a commitment device. Print it, paste it in your trading journal, or set it as your desktop background. The value of having a written protocol is that it removes the decision about whether to follow it.

• Reduce position size to 50% until equity recovers above the daily loss breach level
• Filter entries to confluence setups only — minimum 2 confirming factors required
• No trades in the final 90 minutes of the session during drawdown periods
• Document the specific trigger that caused each loss before entering the next trade
• Set a session loss limit of 60% of the daily limit during recovery mode

Post-Session Trade Review: Build the Feedback Loop FTMO Expects

FTMO’s scaling plan and long-term funded account retention favor traders who demonstrate consistent process, not just profitable months. The traders who get to $200K accounts are the ones who can articulate why they took each trade, what they would change, and what their actual edge is. A post-session AI review builds that articulation systematically.

Paste your trade log — entry, exit, size, market conditions, and your rationale — into a structured review prompt. The model will identify pattern breakdowns, flag where you deviated from your stated rules, and surface which conditions are associated with your winning versus losing trades. Over 30 sessions, this produces a data-driven picture of your actual edge inside FTMO’s evaluation framework.

This is particularly valuable for identifying news-event mistakes, which are one of the most common FTMO breach triggers. If your review log shows consistent losses around NFP and CPI releases, that’s a fixable process problem — not a talent problem.

You are a professional trading coach reviewing my FTMO evaluation session log.
Date: [DATE]. Account: $50,000 FTMO. Session P&L: -$310.
Trades taken: 3. Winners: 1. Losers: 2.
Trade 1: Long GBPUSD, +$180, held 45 min, planned setup executed correctly.
Trade 2: Short USDJPY, -$290, entered against trend after loss on Trade 1, no setup.
Trade 3: Long EURUSD, -$200, entered 20 min before FOMC — news event loss.
Identify the rule and process violations, classify each trade as planned or impulsive,
and give me three specific adjustments for tomorrow's session.

News Event Filter: Protecting Your Evaluation Around High-Impact Data

FTMO does not restrict trading around news events, but the daily loss limit does not care whether your loss came from a technical setup or a 40-pip spike on NFP. High-impact news events — NFP, CPI, FOMC, ECB decisions — produce price action that invalidates most technical strategies and can trigger a daily loss breach in a single candle.

An AI news filter prompt gives you a session-by-session decision framework: which events are on the calendar today, which currency pairs are directly exposed, what the typical pip range for that event has been historically, and whether your current daily drawdown buffer can absorb a worst-case move at your planned position size. This is a five-minute exercise that prevents the most avoidable type of evaluation failure.

The filter is not a blanket ’avoid news’ rule — some traders have genuine edge fading post-news reversals. The prompt helps you define your specific rule: no new positions 15 minutes before and 10 minutes after high-impact events affecting your traded pair, with a hard exception only if equity buffer exceeds X% of daily limit.

• Identify all high-impact events (red folder on Forex Factory) for the session
• List which currency pairs in your watchlist are directly affected
• Calculate worst-case drawdown at planned size given average event pip range
• Apply your pre-defined rule: close, flatten, or avoid new entries in the event window
• Log every news event decision in your trade journal regardless of outcome

Position Sizing Calculator Prompt: Never Guess Your Lot Size Again

FTMO’s daily loss limit creates a hard ceiling on risk per trade that most traders calculate inconsistently. If you’re 60% through your daily limit and still have two sessions of trading ahead, your per-trade risk isn’t 1% of account — it’s a fraction of the remaining $200 buffer. Lot size needs to be recalculated dynamically, not set once at the start of the week.

A position sizing prompt takes your current equity, remaining daily drawdown, stop loss in pips, and the currency pair’s pip value and returns the exact maximum lot size that keeps you within FTMO rules. This eliminates rounding errors and the cognitive load of doing pip-value math on pairs like USDJPY and GBPJPY, where pip values are non-intuitive.

Run this calculation before every single trade entry. The 15 seconds it takes to paste your inputs and read the output is the cheapest risk management available to any FTMO trader.