AI Prompt Library for Crude Oil (WTI) Trading

WTI crude oil moved more than 40% in a single calendar year three times between 2014 and 2024. Each swing was driven by a distinct catalyst — OPEC+ quota decisions, U.S. shale production data, dollar strength, and geopolitical disruption in the Strait of Hormuz. The traders who captured those moves weren’t faster; they were better prepared. AI gives you the preparation infrastructure.

Crude oil is not a single-variable market. It responds simultaneously to EIA inventory reports, Federal Reserve rate decisions, Chinese manufacturing PMI, and tanker traffic data. Generic research workflows collapse under that complexity. A prompt library built specifically for WTI forces AI to work within the correct analytical frame — not a generalized one.

This page gives you a structured library of AI prompts engineered for WTI crude oil. Each prompt targets a specific research task: supply-demand modeling, OPEC scenario analysis, technical pattern interpretation, and risk framing. Use them directly in ChatGPT, Claude, or any LLM. Adapt them to your position size and time horizon.

Why WTI Demands Its Own Prompt Architecture

WTI crude oil trades on the NYMEX and serves as the U.S. benchmark, priced at the Cushing, Oklahoma delivery hub. That geography matters. Cushing pipeline capacity constraints have historically created disconnects between WTI and Brent that caught traders off guard — including the April 2020 negative price event, when front-month WTI futures settled at -$37.63 per barrel. Generic commodity prompts don’t account for Cushing dynamics.

The EIA releases Weekly Petroleum Status Reports every Wednesday at 10:30 AM ET. Those reports move WTI by $1-3 per barrel on average when the inventory build or draw deviates significantly from consensus. A prompt library built for WTI should include pre-report framing, post-report interpretation, and positioning logic — all calibrated to WTI’s specific volatility profile, not a generalized energy sector template.

Beyond inventory data, WTI pricing is structurally linked to the U.S. dollar index (DXY), OPEC+ production quota decisions, and U.S. shale rig count data published by Baker Hughes every Friday. Your AI prompts need to pull all three threads simultaneously to deliver actionable analysis.

• Cushing hub storage levels — the physical constraint that drives WTI-specific dislocations
• EIA Wednesday inventory reports — the highest-impact weekly event for WTI traders
• Baker Hughes rig count — leading indicator for U.S. production trajectory
• OPEC+ quota decisions — the single most impactful geopolitical variable for global crude pricing
• DXY correlation — dollar strength inversely pressures WTI denominated in USD
• Chinese import data — demand-side signal with a 6-8 week lag effect on spot prices

Supply Shock Analysis Prompts

Supply shocks are the defining event type for WTI traders. Whether it is a Saudi Aramco facility attack, a Gulf of Mexico hurricane, or an unexpected OPEC+ cut announcement, the price response is fast and the window for positioning is narrow. The prompt below forces AI to structure a supply shock analysis with the specificity WTI requires.

The key variable most traders miss in supply shock analysis is duration. A 500,000 barrel-per-day production cut that lasts 30 days has a fundamentally different price implication than one lasting six months. The prompt below builds duration sensitivity into the output from the start, preventing the AI from returning a flat, single-scenario response.

You are an energy markets analyst specializing in WTI crude oil fundamentals.
A supply disruption has reduced global crude output by [X] million barrels per day.
The disruption source is [OPEC+ voluntary cut / geopolitical event / weather / infrastructure].
Current Cushing storage is [above / below / at] the 5-year seasonal average.
Analyze the price impact on WTI across three time horizons: 30 days, 90 days, and 6 months.
For each horizon, specify the likely price range, the key variable that could invalidate the bullish case, and the equivalent move in crude oil options implied volatility.

OPEC+ Decision Interpretation Prompts

OPEC+ meetings produce outcomes that range from full compliance enforcement to surprise production increases. The market’s reaction is rarely a clean read of the headline number. In June 2023, OPEC+ announced a voluntary cut of 1 million barrels per day from Saudi Arabia — WTI initially rallied, then gave back all gains within a week as traders priced in compliance skepticism and demand weakness from China.

The prompt below is designed for use immediately after an OPEC+ communiqué drops. It separates the headline from the structural signal, which is where the tradeable edge lives. Feed the actual OPEC+ statement text into the prompt for highest precision output.

Note: Always cross-reference AI output against the OPEC Monthly Oil Market Report, which provides the official production baseline data. The AI’s analysis is only as accurate as the data you provide in the prompt context.

You are an OPEC+ policy analyst covering WTI crude oil market implications.
The following is the full text of the latest OPEC+ communiqué: [PASTE TEXT HERE].
Identify: (1) the net change in production quota versus the prior agreement, (2) which member countries carry the largest compliance risk based on recent output history, (3) the implied price floor Saudi Arabia appears to be defending based on the cut magnitude, and (4) the asymmetric trade setup for WTI in the 2-week window following this announcement.

EIA Report Pre- and Post-Analysis Prompts

The EIA report is WTI’s highest-frequency fundamental catalyst. Consensus estimates are published by Bloomberg and Reuters the day before release. The trade is not in the number — it is in the deviation from consensus and the narrative shift it forces. A 4-million-barrel inventory draw when consensus expected 1.5 million is a different signal than the same draw when consensus expected 5 million.

Use the pre-report prompt the evening before each Wednesday release to frame your positioning thesis. Use the post-report prompt within 15 minutes of the 10:30 AM release to stress-test whether your thesis remains intact or requires adjustment.

You are a WTI crude oil trader preparing for the weekly EIA Petroleum Status Report.
Current market context: WTI spot price is $[X], consensus inventory estimate is [+/-Y] million barrels, the 4-week average has shown [builds / draws], and Cushing stocks are [X]% [above / below] the 5-year average.
Generate: (1) the three most likely report outcomes and the expected WTI price reaction for each, (2) the implied volatility move a trader should anticipate for front-month futures, (3) a stop-loss placement rationale for a long or short position entered pre-report, and (4) the secondary data point in the report most likely to modify the initial price reaction within 60 minutes of release.

Technical Pattern Prompts Calibrated to WTI Behavior

WTI crude oil has well-documented behavioral tendencies around specific price levels. The $60, $70, $80, and $100 per barrel levels have historically attracted options hedging activity from producers and airlines, creating support and resistance clusters that are structurally different from momentum-driven breakout zones. Technical analysis on WTI needs to account for this hedging-driven price magnetism.

The prompt below is designed for traders using price action signals. It frames technical patterns within the fundamental context that determines whether a signal has structural confirmation or is likely to be a false breakout. WTI false breakouts above $80 in 2023 cost momentum traders significant drawdown — the prompt below is built to flag that risk explicitly.

Feed actual OHLCV data or a chart description into this prompt. The more specific your input, the more precise the AI output. Vague inputs produce vague outputs.

• Specify the timeframe: intraday scalp, swing (3-10 days), or macro trend (weeks to months)
• Include the nearest key level — $5 increments carry the most hedging activity
• Reference current term structure: contango vs. backwardation changes breakout probability
• Note the VIX environment — high equity volatility correlates with WTI correlation breakdown
• Always include the DXY trend — dollar direction is the fastest technical invalidation signal

Risk Framing Prompts for WTI Positions

Crude oil carries a realized volatility that averages 30-40% annualized, with spikes above 80% during major supply events. Position sizing that works for equities will overtrade WTI. The prompt below generates a complete risk framework for a WTI position, including position sizing, maximum drawdown tolerance, and scenario-based stop logic.

Risk framing is not a defensive exercise — it is an offensive one. Knowing your maximum loss in the bear case frees you to hold a position through normal volatility without premature exit. The traders who held long WTI positions through the 2021-2022 run from $47 to $130 required exactly this kind of pre-defined risk architecture to avoid being stopped out during the 15-20% corrections that occurred along the way.

You are a risk manager specializing in commodity futures with a focus on WTI crude oil.
I am considering a [long / short] position in WTI crude oil futures.
Entry price: $[X]. Account size: $[Y]. Maximum acceptable loss: [Z]%.
Current annualized realized volatility for WTI is approximately [30-40]%.
Generate: (1) recommended position size in contracts based on the risk parameters, (2) initial stop-loss level with justification, (3) the three macro scenarios that would invalidate the trade thesis and require immediate position review, and (4) the time decay of the trade thesis — at what point does a non-moving market become a reason to exit?