Spot Hidden Support and Resistance Before You Trade
Find the price zones that matter most before turning a chart screenshot into a trade idea.
Prompt Overview
Featured AI Partner
Tips For You
Ask for zones, not perfect lines. AI vision is more useful when it helps you see structure than when it pretends to know exact executable prices from an image.
From Operations TeamNexusAi TechnologyProblem It Solves
Many weak trades fail because the trader enters near an obvious resistance zone, ignores nearby support, or treats an exact line as stronger than a zone. This prompt focuses only on practical level mapping.
Zone-Based Level Mapping
Identifies support and resistance as practical reaction areas instead of fragile single lines.
Strength Scoring
Ranks zones by visible evidence and repeated market reaction.
Invalidation Logic
Shows what would weaken or break each level-based idea.
Journal-Ready Checklist
Turns the chart read into a quick pre-trade review habit.
AI Prompt Instructions
Act as a technical chart-mapping assistant. Review the uploaded chart screenshot and identify the most important visible support, resistance, supply, demand, and pivot zones. Your job is not to predict price direction. Your job is to help me map where price may react and what levels require verification.
Start by reading the chart visually. Identify repeated rejection zones, repeated bounce zones, consolidation boundaries, swing highs, swing lows, prior breakout levels, failed breakout areas, moving-average interaction if visible, and round-number zones if prices are readable. If exact prices are not readable, describe zones by their position on the chart and instruct me to confirm exact values in TradingView.
Create a table with: Level or Zone, Evidence Seen on Screenshot, Strength Rating from 1 to 5, Why It Matters, What Would Confirm It, What Would Invalidate It. Avoid false precision. Prefer zones over exact single prices unless the screenshot clearly shows exact values.
Then list three possible trader mistakes caused by misreading these levels, such as entering into resistance, placing stops inside normal volatility, ignoring a retest, chasing after a late breakout, or confusing a weak level with a major level.
End with a short checklist I can paste into a trading journal before making any decision: higher timeframe confirmation, volume confirmation, catalyst check, risk/reward check, and invalidation check.
Quality controls: Keep the analysis practical, neutral, and screenshot-grounded. Do not invent exact prices, indicator settings, earnings dates, news, options data, or volume numbers that are not visible. If the image is blurry, cropped, or missing the right axis, say what cannot be confirmed. Use cautious language such as appears, suggests, visible on the screenshot, and requires confirmation. End by reminding me that the output is a chart-analysis aid, not a trading signal, and that every level must be checked against live market data before use.
Expected Outcome
A practical support and resistance map with zone strength, evidence, confirmation triggers, invalidation triggers, and common level-reading mistakes.
Implementation Journey
Upload the chart and paste the prompt
Open ChatGPT Vision, Claude, or Gemini, upload the chart screenshot first, then paste the promptText with the ticker, timeframe, asset type, and your trading style. Expect a structured chart-read, not a trade instruction.
3-5 minutesCross-check with market data
Take the output into TradingView, your broker chart, StockIntent, Tykr, or another research tool to verify price levels, volume context, indicators, and recent news before using the analysis.
5-10 minutesConvert the output into a trading note
Paste the AI output into Notion, a spreadsheet, or your trade journal. Record the setup, invalidation level, risks, and follow-up checks so the result becomes a repeatable review workflow.
5 minutes
