AI Prompt Library for Day Traders

Day traders make an average of 33 decisions per session. Most of those decisions happen in seconds, under conditions that systematically degrade judgment — noise, recency bias, P&L anxiety. AI doesn’t eliminate those pressures, but a well-structured prompt forces you to frame the trade before you take it, which is where most edge is actually lost.

The gap between traders who use AI effectively and those who don’t isn’t access — it’s structure. Typing ’analyze NVDA’ into ChatGPT returns a generic summary. Feeding it a precise, context-loaded prompt returns a directional framework you can act on. That distinction compounds across 20 trading days.

This library gives day traders the exact prompts to run at each stage of the session: pre-market preparation, intraday setup scanning, position sizing, trade journaling, and post-session review. Each prompt is designed to extract specific, actionable output — not commentary.

Why Generic AI Prompts Fail Day Traders

Day trading is a time-compressed discipline. Your pre-market window might be 45 minutes. Your decision on a momentum trade might be 8 seconds. Generic prompts return generic output — broad market takes, hedged language, and no clear directional stance. That’s useful for investors with a 12-month horizon. It’s a liability for a trader managing a position in real time.

The prompts that actually move the needle are ones that constrain the AI’s response space. You’re not asking for an opinion on the market — you’re asking for a structured analysis of a specific ticker, a specific catalyst, and a specific technical level. The more specific the input, the more executable the output.

Every prompt in this library follows a three-part structure: context (what you’re looking at), constraint (what the AI should and shouldn’t consider), and output format (exactly how you want the answer delivered). That format turns AI from a research assistant into a structured thinking partner.

• Vague prompts produce hedged, unusable analysis
• Time-constrained sessions require prompts that load fast and return clean output
• Structured prompts reduce cognitive load at the moment of decision
• Repeatable prompt formats build a consistent trading process over time

Pre-Market Preparation Prompts

Pre-market is where the session is won or lost. Traders who enter the open without a defined watchlist, clear levels, and a read on macro catalysts are reacting — not executing a plan. A well-run pre-market prompt session takes under 20 minutes and produces a structured game plan for the day.

The prompt below is designed for a single-ticker deep dive. Run it on your top 2-3 names before the open. It pulls together catalyst context, technical structure, and a bias statement — the three inputs you need before size goes on.

You are a professional day trader preparing for the market open.
Ticker: [TICKER]
Catalyst: [earnings / macro event / sector news — describe in one sentence]
Key levels: [support 1], [support 2], [resistance 1], [resistance 2]
Pre-market price action: [up/down X% on Y volume]

Give me: (1) a one-sentence directional bias and the condition that invalidates it, (2) the highest-probability setup for the first 30 minutes, and (3) the level I should not be long above / short below. Be direct. No caveats.

Intraday Setup Identification Prompts

Once the session is live, the job shifts from preparation to pattern recognition. Momentum setups, opening range breakouts, VWAP reclaims, failed breakdowns — each has a distinct structural fingerprint. The AI prompt below is designed to evaluate whether a live setup meets your criteria, not to generate a new idea from scratch.

Feed it your real-time observations — price relative to VWAP, volume character, time of day, and the specific pattern you’re watching. The output is a quick-pass/fail assessment against a defined setup template, which keeps you from rationalizing marginal entries.

Use this prompt between 9:45 and 11:00 AM when intraday momentum setups are highest probability. After 11:30, adjust your input parameters to account for lower volume and wider spreads.

I'm evaluating an intraday trade setup. Here are the current conditions:
Ticker: [TICKER] | Time: [TIME] | Price: [PRICE] | VWAP: [VWAP level]
Volume vs. average: [above/below — by how much]
Pattern: [e.g., bull flag on 5-min, VWAP reclaim, ORB breakout]
Catalyst still active: [yes/no]

Score this setup on three dimensions (1-5 each): setup quality, timing quality, risk/reward at current price. Then give me a one-line entry trigger and the exact stop level. If the setup scores below 10 total, tell me to pass.

Position Sizing and Risk Management Prompts

Position sizing is where most day traders bleed performance — not in setup selection. A 60% win rate with inconsistent sizing produces worse outcomes than a 50% win rate with disciplined risk per trade. The prompt below calculates your position size given your account parameters and the specific trade’s stop distance.

Run this before every entry. It takes 30 seconds and removes the in-the-moment temptation to size up on conviction. Conviction is not edge. Defined risk per trade is edge.

• Input your account size and max risk per trade as fixed parameters
• Include the distance from entry to stop in dollar terms, not percentage
• Ask for share count, not just dollar exposure — execution happens in shares
• Flag if the resulting position is too large for the average daily volume of the ticker

Calculate my position size for the following trade:
Account size: $[AMOUNT] | Max risk per trade: [X]% of account
Entry price: $[ENTRY] | Stop price: $[STOP]
Ticker average daily volume: [ADV]

Return: (1) maximum share count based on risk parameters, (2) total dollar exposure, (3) whether this position size is liquid given ADV — flag if my position exceeds 1% of ADV. Show your math.

Trade Journaling Prompts for Pattern Recognition

A trade journal that only records entries and exits is an expense ledger. A journal that records decision quality — the setup, the thesis, the execution grade, and the lesson — is a compounding asset. Most traders skip journaling because the blank page is friction. A structured prompt eliminates that friction.

The prompt below generates a complete journal entry from your raw trade notes. Feed it messy inputs — time, price, what you were thinking — and it returns a structured entry you can actually analyze at the end of the week.

Over 20 trading days, structured journal entries reveal behavioral patterns that P&L alone can’t surface: specific times of day where your execution degrades, setups you consistently overtrade, and the emotional states that precede your largest losses.

Convert my raw trade notes into a structured journal entry.
Raw notes: [paste your notes — messy is fine]

Format the output as: Setup Type | Entry Trigger | Exit Trigger | Result ($) | Execution Grade (A/B/C/F) | What I did well | What I'd change | Behavioral flag (if any — e.g., revenge trade, FOMO entry, held past stop). Keep it under 150 words.

Post-Session Review Prompts

The 15 minutes after the close is the highest-leverage time in a trader’s day. P&L is final. The decisions are recent enough to reconstruct. And you’re not in a live position, which means your thinking is cleaner. Most traders skip this entirely, which is why the same mistakes recur for months.

The prompt below runs a structured debrief on your session. It pulls your best and worst trades, evaluates process against outcome, and generates one specific adjustment for tomorrow’s session — not a list of ten things to fix, which produces no change at all.

Consistency in post-session review is the single highest-correlation variable between traders who improve and those who plateau. The prompt below makes it repeatable.

• Review process quality separately from P&L — a losing trade can be a good process
• Identify the single largest decision error of the session, not a comprehensive list
• Generate one rule adjustment, not a full process overhaul
• Track whether your pre-market bias was correct — accuracy compounds into pattern recognition