AI Prompt Library for Swing Traders

Swing traders hold positions for two to ten days on average — long enough to need a thesis, short enough that a single missed signal costs real money. Studies of retail trading behavior show that inconsistent pre-trade analysis, not bad luck, accounts for the majority of avoidable losses in this timeframe. The edge is not in finding more setups. It is in processing the ones you already see with greater precision.

AI language models have changed the economics of that analysis. A prompt-driven workflow can compress two hours of sector rotation research, earnings calendar cross-referencing, and technical level mapping into under fifteen minutes. The variable is prompt quality. Generic inputs produce generic output — noise dressed up as insight. Swing traders need prompts engineered for their specific holding period, risk structure, and decision cadence.

This library gives you exactly that. Each prompt below is built for the swing trading context: multi-day holds, defined risk-reward thresholds, catalyst-driven timing, and weekly review cycles. Use them as-is or adapt them to your watchlist methodology.

Why Generic AI Prompts Fail Swing Traders

Most AI trading prompts circulating online are written for day traders or long-term investors. Day trader prompts optimize for intraday momentum and tape reading cues that are irrelevant on a four-day hold. Investor prompts focus on fundamental thesis construction over quarters, not catalysts resolving in a week. Swing traders operate in the gap between those two timeframes — and that gap has its own logic.

A swing trade lives and dies on catalyst timing, sector relative strength, and the distance between current price and the next structural level. A prompt that does not anchor to those three variables will return analysis that sounds informed but does not help you size, time, or exit the trade. The prompts in this library are written with that constraint explicit in every instruction.

The second failure mode is vagueness. Asking an AI to ’analyze this stock’ returns a summary. Asking it to ’identify the nearest support and resistance levels on a daily chart given these price points, then calculate the risk-reward ratio at a stop below the last swing low’ returns a decision input. Specificity is the entire mechanism.

• Day trader prompts ignore multi-day holding cost and overnight risk
• Investor prompts miss near-term catalyst windows critical to swing timing
• Vague prompts produce summaries, not actionable trade parameters
• Swing-specific prompts must reference: catalyst date, key levels, sector context, and R:R ratio

Pre-Trade Analysis Prompt: Build Your Setup Brief

Before entering a swing trade, you need a one-page brief covering the catalyst, the technical structure, and the invalidation level. This prompt generates that brief in under two minutes. Feed it the ticker, the catalyst date if one exists, and the price levels you have already identified. The AI handles the synthesis.

This prompt is designed for use after your initial scan — not as a replacement for it. You bring the watchlist candidate. The prompt structures the case for or against pulling the trigger. Run it on every A-grade setup before entry to enforce consistency across your decision-making.

Act as a professional swing trader preparing a pre-trade brief.
Ticker: [TICKER]
Current price: [PRICE]
Key support: [LEVEL] | Key resistance: [LEVEL]
Catalyst or event date: [DATE or 'none identified']
Sector: [SECTOR]

Provide: (1) a one-paragraph technical setup summary referencing the price levels above, (2) the primary catalyst or momentum driver for a 3-7 day hold, (3) the trade invalidation level and why it matters structurally, (4) a risk-reward assessment assuming a stop at the invalidation level and a target at resistance. Be direct. Flag any setup weakness explicitly.

Sector Rotation Prompt: Find Where the Money Is Moving

Swing trading against sector momentum is one of the most consistent ways to underperform. A technically perfect setup in a sector that institutions are rotating out of will grind sideways or fail outright. Before committing to any position, you need a current read on which sectors are attracting capital and which are being distributed.

This prompt works best when you feed it recent price performance data for the major sector ETFs — XLK, XLF, XLE, XLV, XLI, and so on. You can pull one-week and one-month returns in under three minutes from any screener. Paste that data in and let the model identify the rotation trend and flag where swing setups are most likely to have institutional tailwind behind them.

You are a sector analyst helping a swing trader identify current capital rotation.
Below is one-week and one-month performance data for major sector ETFs:
[PASTE ETF PERFORMANCE DATA]

Analyze: (1) which two or three sectors show the strongest short-term momentum relative to the one-month trend, (2) which sectors appear to be in distribution, (3) whether the rotation pattern suggests risk-on or risk-off positioning, (4) which sector offers the highest-probability environment for a 3-7 day long swing trade this week. Be specific. Reference the data provided.

Entry Timing Prompt: Narrow the Window

Identifying a setup and timing the entry are two different skills. Swing traders who enter too early absorb unnecessary drawdown. Those who wait for full confirmation often chase extended moves with compressed upside. The optimal entry is at the first low-risk inflection point after the catalyst or technical trigger confirms.

This prompt asks the AI to behave as an entry timing specialist. Give it your setup parameters, the current price action description, and the timeframe you are monitoring for the trigger. It will return a specific entry condition — not ’wait for a pullback’ but ’wait for a close above [level] on above-average volume following a consolidation of at least two candles.’

You are an entry timing specialist for swing trades with 3-7 day hold targets.
Setup: [DESCRIBE THE SETUP IN ONE SENTENCE]
Current price action: [DESCRIBE WHAT THE CHART IS DOING NOW]
Trigger timeframe: [DAILY / 4H]
Risk tolerance: [% of account or dollar amount]

Define: (1) the precise entry condition that confirms the setup without chasing, (2) the ideal entry price range and why, (3) the maximum acceptable entry distance from the stop level to maintain a minimum 2:1 risk-reward, (4) one condition that would invalidate the entry before execution. Give exact, actionable language — no generalizations.

Weekly Trade Review Prompt: Build the Feedback Loop

The difference between swing traders who compound gains over time and those who plateau is the quality of their review process. A review that only logs wins and losses misses the mechanism. You need to know whether losses came from poor setup selection, poor entry timing, poor position sizing, or external factors outside the model — because each has a different fix.

Run this prompt every weekend on the week’s closed trades. Feed it the trade log data: ticker, entry, exit, stop, result, and a brief note on what you were thinking at entry. The AI will categorize the errors, identify patterns across multiple trades, and return a prioritized list of the one or two process improvements most likely to move your expectancy.

• Log every closed trade: entry price, exit price, planned stop, actual stop, result in R
• Note the original thesis at entry — one sentence is enough
• Flag whether the trade was exited per plan or deviated, and why
• Include any trades you passed on that set up correctly — missed opportunity data matters
• Run the review prompt on a minimum of three trades for pattern detection to be meaningful

You are a trading coach conducting a weekly performance review for a swing trader.
Trade log for the week:
[PASTE TRADE DATA: TICKER, ENTRY, EXIT, STOP, RESULT, ENTRY THESIS]

Analyze: (1) categorize each loss by error type — setup quality, entry timing, position sizing, or external factor, (2) identify any repeated pattern across winning or losing trades, (3) rate overall process discipline on a 1-10 scale with specific justification, (4) recommend one concrete adjustment to the entry criteria and one to the exit criteria based solely on this week's data. Be direct and critical where the data warrants it.

Position Sizing Prompt: Protect the Account First

Swing traders operating without a systematic position sizing framework are running an inconsistent risk profile across trades — sometimes risking 0.5% of account, sometimes 3%, with no logic governing the difference. That inconsistency destroys expectancy even when the setup win rate is solid. A consistent 1% risk-per-trade framework across all positions is the baseline. The prompt below enforces that baseline automatically.

Feed it your account size, your defined stop level, and your entry price. It returns the exact share count that keeps risk at your specified percentage. It also flags when a setup’s required stop distance makes the position size impractically small — a signal that the setup itself may not fit your account size at current volatility levels.

You are a position sizing calculator for a swing trader.
Account size: $[AMOUNT]
Max risk per trade: [1% or custom %]
Ticker: [TICKER]
Entry price: [PRICE]
Stop loss level: [PRICE]

Calculate: (1) the dollar amount at risk based on the stop distance, (2) the exact share count to stay at or below the max risk percentage, (3) the notional position size and what percentage of account it represents, (4) flag if the position would require margin or if the stop distance implies volatility outside normal swing trade parameters for this account size.