This guide provides a comprehensive overview of every feature within the “Scan Sensor” TradingView indicator. Learn how to interpret its visuals, configure its settings, understand its sophisticated scoring engine, and apply practical strategies.
The Scan Sensor is an advanced, multi-faceted TradingView indicator designed as a comprehensive decision-support tool. Its primary goal is to efficiently analyze market data to identify high-probability trade setups ripe for further investigation.
It achieves this by:
Analyzing dozens of technical indicators across six key categories: Momentum, Trend, Volatility, Volume, Price Action, and Divergence.
Calculating a weighted “Elite Score” (0-100) that quantifies the quality of the current setup based on confluence across these categories.
Determining the current “Market Regime” (e.g., Trending, Ranging, High Volatility) to provide crucial context.
Applying smart filters (Time-of-Day, News Hours, Liquidity), dynamic multipliers (based on regime), and penalties (for unfavorable conditions) to refine the score.
Generating a clear “SCAN NOW” signal when the final Elite Score surpasses a dynamically calculated, volatility-adjusted threshold, indicating it’s time to run a deeper scan or analysis.
When added to your chart, the Scan Sensor displays several key visual components:
These colored vertical bands highlight bars where specific score conditions are met:
Green Bands: Appear on bars where the scan_signal_final condition is true. This signifies a fully confirmed “SCAN NOW” signal, meeting all score, filter, and cooldown criteria.
Yellow/Gold Bands: Appear on bars where the elite_score is high (≥ 90% of the required adaptive_threshold) but the signal is not yet final (e.g., filters not passed, or cooldown active). This visually represents the “⏳ BUILDING” state, indicating a potential setup is forming and warrants close attention.
These appear on top of the background bands when a scan_signal_final is generated:
“SCAN NOW” Label: A green text label appearing below the signal bar.
Tiered Markers (Icons): Plotted above the signal bar, these icons grade the strength or quality of the “SCAN NOW” signal based on the Elite Score achieved:
💎 “ELITE” (Score 90+): Highest conviction signal.
🔥 “PLATINUM” (Score 80-89): Very strong signal.
✨ “GOLD” (Score 70-79): Solid, high-quality signal.
🟢 “QUALITY” (Score < 70): The signal met the minimum threshold but is less statistically robust than higher tiers.
This dashboard provides a real-time summary:
ELITE SCORE: The current score (0-100), color-coded from red (low) to bright green (high).
Signal Status: Indicates the current state:
🚀 SCAN NOW: A final signal is active on the current bar. Time to investigate further!
⏳ BUILDING: Score is high (≥ 85% of threshold) and approaching signal criteria. Pay attention.
⚡ WAIT: Score is moderate; conditions are not yet favorable.
❌ NO SETUP: Conditions are poor; no quality setup detected.
Confidence: An “AI Confidence” rating (Very High, High, Medium, Low). This reflects how many of the six scoring categories strongly support the current score. “Very High” means multiple categories (e.g., Trend, Volume, and Momentum) are in strong agreement.
Threshold: The exact Elite Score required to trigger a “SCAN NOW” signal on the current bar. This value changes dynamically if “Adaptive” mode is enabled.
If Show Market Regime is enabled, this section provides vital market context:
Phase: Wyckoff-inspired market phase (Accumulation, Markup, Distribution, Markdown, Neutral) based on price, volume, and OBV analysis.
Trend: Current trend strength and direction (Strong Uptrend, Strong Downtrend, Weak Trend, Ranging) based primarily on ADX.
Volatility: Market volatility level (High Vol, Normal Vol, Low Vol) derived from the ATR percentile.
Volume: Volume activity (Climax, High, Normal, Low) compared to its recent average (20-period SMA).
Position: How far the current price is from its medium-term mean (50 EMA), indicating if it’s potentially “Extended” or “Stretched”.
If Show Signal Breakdown is enabled (highly recommended), this table appears on the last bar and details how the Elite Score is calculated:
Category Scores: Shows points awarded for each of the six core analysis categories:
Momentum (max 30 pts)
Trend Alignment (max 25 pts)
Volatility Opportunity (max 20 pts)
Volume Validation (max 15 pts)
Price Action Quality (max 10 pts)
Divergence Premium (max 15 pts)
Modifiers:
Penalties: Points deducted for unfavorable conditions (e.g., low volume if min_liquidity_filter is on, choppy market, price being overextended, trading against higher timeframe trends).
Regime Bonus: A percentage boost applied to the score when trading in highly favorable market regimes (e.g., Markup/Markdown phases, Strong Trend).
Key Signals: Flags specific high-impact events detected on the current bar, which contribute significantly to the score (e.g., 🔄 Divergence, 📊 Engulfing Candle, 💥 BB Squeeze Breakout, 📈 Volume Climax, ✓ MTF Alignment).
When Show AI Confidence Bands is enabled and a “SCAN NOW” signal occurs, two bands appear slightly above and below the signal bar’s high/low.
Color: Reflects the “AI Confidence” level (Green = Very High, Yellow = High, Orange = Medium/Low).
Purpose: These bands represent a volatility-adjusted price range based on the signal bar’s context. They can offer potential areas of interest for support/resistance or invalidation levels during further analysis.
When Show Opportunity Heatmap is enabled, three key price zones are drawn extending to the right from the last bar:
Support Zone (Green): Calculated based on the most recent significant swing low, adjusted by the current ATR.
Resistance Zone (Red): Calculated based on the most recent significant swing high, adjusted by the current ATR.
VWAP Zone (Blue): A narrow zone centered around the current Volume Weighted Average Price (VWAP).
Purpose: These zones highlight potential areas where price might react, serving as points of interest for monitoring price action during deeper analysis.
Customize the Scan Sensor’s behavior via the “Settings” menu:
Signal Mode (Crucial): Controls the sensitivity and the adaptive_threshold required for a signal.
Adaptive (Default): The threshold changes automatically based on market volatility (ATR Percentile). It requires a higher score (75.0) in low volatility (fewer, higher-quality signals) and a lower score (55.0) in high volatility (more frequent signals). Normal volatility uses 65.0.
Ultra Conservative: Fixed threshold of 85.0. Needs extremely strong confluence.
Conservative: Fixed threshold of 75.0.
Balanced: Fixed threshold of 65.0.
Aggressive: Fixed threshold of 50.0. Signals on weaker confluence, requires more discretion.
Display: Checkboxes to toggle the visibility of all the on-chart elements described above (Score Table, Breakdown Table, Heatmap, Regime Table, Confidence Bands).
Smart Filters:
Enable Time-of-Day Filter: If checked, suppresses signals during typically low-liquidity periods (defined in the code, e.g., 0:00-3:00 and 12:00-13:00 based on chart time).
Avoid Major News Hours: If checked, suppresses signals 30 minutes before and after predefined major economic release times (UTC based).
Minimum Liquidity Filter: If checked, applies a significant “Penalty” to the score if the current volume is extremely low compared to its average (specifically, < 50% of the 20-period SMA), helping to avoid signals in illiquid conditions.
Multi-Timeframe Analysis: Define up to three higher timeframes (HTF 1, HTF 2, HTF 3). The indicator checks if the current price/trend aligns with the EMA trends and conditions (like RSI, ADX) on these HTFs. Strong alignment significantly boosts the “Trend Alignment” score, while misalignment applies a “Penalty”.
The Elite Score is meticulously calculated by summing points from 6 categories, then applying multipliers and penalties.
Momentum Confluence (Max 30 pts): Rewards agreement between RSI (including smoothing & change), MACD (crossovers & histogram expansion), Stochastics (oversold/overbought crosses), and MFI (Money Flow Index).
Trend Alignment (Max 25 pts): Awards points for:
Clean EMA alignment (“Cascade”: e.g., Price > 9EMA > 21EMA > 50EMA).
Strong trend confirmation via ADX (> 25 and rising) coupled with directional confirmation (+DI vs -DI).
Confluence across the user-defined Higher Timeframes (HTFs). Trading in the direction of HTF trends earns significant points.
Volatility Opportunity (Max 20 pts): Looks for signs of potential volatility expansion:
Bollinger Band Squeeze: Price consolidating inside Keltner Channels while outside Bollinger Bands, especially if bandwidth percentile was previously low (< 20) and is now expanding.
ATR Expansion: Current ATR significantly larger than recent ATRs, indicating volatility increase.
Favorable Volatility Regime: Bonus points for operating in “High Vol” or “Normal Vol” regimes.
Volume Validation (Max 15 pts): Confirms price action with volume:
Volume Surge: High points for “Climactic” volume (> 2.5x SMA) or significant increases over the average.
Smart Money Flow: Points awarded if CMF (Chaikin Money Flow) and OBV (On Balance Volume) directionally agree (e.g., CMF > 0.2 and OBV rising).
Accumulation/Distribution Confirmation: Checks if the A/D line confirms recent price trends.
Price Action Quality (Max 10 pts): Looks for specific candlestick patterns and key level interactions:
Candlesticks: Points for high-probability reversal/continuation candles like Hammers, Shooting Stars, and Engulfing patterns.
Key Level Interaction: Points if price is interacting cleanly with recent Pivot Highs/Lows or the VWAP.
Divergence Premium (Max 15 pts): Adds a significant score boost if divergence is detected:
Regular Bullish/Bearish RSI Divergence (Highest premium).
Hidden Bullish/Bearish RSI Divergence (Continuation signal).
MACD Histogram Divergence.
Modifiers (Applied After Category Sum):
Regime Multiplier: The total score is boosted if the current Market Phase (“Markup”, “Markdown”, “Accumulation”, “Distribution”) or Trend Regime (“Strong Uptrend/Downtrend”) is highly favorable for a potential move.
Penalties: The score is reduced for negative factors:
Low Liquidity (if filter enabled).
Choppy/Ranging Market (low ADX & low BB Width percentile).
Overextended Price (far from 50 EMA).
Trading Against Higher Timeframes.
The Final Signal (“SCAN NOW”) is generated only if Elite Score >= Adaptive Threshold, all enabled Smart Filters pass, AND a Cooldown period (10 bars) since the last signal has elapsed.
The Scan Sensor’s primary purpose is not to provide direct entry/exit signals but to alert you when conditions are favorable to conduct a deeper scan or analysis. It flags moments of high confluence.
Wait for a 🚀 “SCAN NOW” signal (Green Background Band + Label + Marker).
IMMEDIATELY Qualify the alert using the tables:
Score & Tier: Is it 💎/🔥/✨? Higher scores suggest stronger confluence.
Confidence: Is it “Very High” or “High”? Confirms broad-based strength.
Regime Table: Does the signal align with the Market Phase and Trend? (e.g., a Bullish “SCAN NOW” during “Markup” and “Strong Uptrend” is ideal). Be wary of signals opposing the regime (counter-trend).
Breakdown Table: Why did it signal? Look for high scores across multiple categories, especially Trend, Divergence, and Volatility. Check for significant Penalties. What are the Key Signals listed?
Position: Is the price “Extended”? An extended signal might suggest waiting for a pullback before deeper analysis.
Action: If the qualified alert looks promising, initiate your detailed scanning process or switch to a dedicated analysis tool (like the “Live Market Analysis”) for that specific asset and timeframe.
Monitor for the ⏳ “BUILDING” status in the Score Table (or the Yellow/Gold Background Band).
Check the Breakdown Table: Identify which categories are scoring highly and what “Key Signals” are present. This tells you what kind of setup might be forming (e.g., Divergence-based, Squeeze-based).
Action: Prepare to run your detailed scan on the next bar(s) if the conditions continue to improve and potentially trigger a full “SCAN NOW” signal.
Enable the Opportunity Heatmap.
Observe the Support, Resistance, and VWAP zones on the far right of the chart.
Look for “SCAN NOW” signals occurring at or very near these zones.
Example: Price pulls back into the green Support Zone, stalls, and then a high-scoring, high-confidence Bullish “SCAN NOW” signal appears. This confluence increases the probability that the support level might hold and warrants a deeper scan for a potential long setup.
Action: Use zone interaction combined with Scan Sensor alerts to prioritize which assets to analyze further.
Automate your monitoring by creating TradingView alerts based on the Scan Sensor signals:
Click the “Alert” (alarm clock) icon on your TradingView chart.
In the “Condition” dropdown, select “Scan Sensor”.
Choose the specific alert condition you want:
“🚀 SmartSense: ELITE SETUP DETECTED”: Fires on any final “SCAN NOW” signal. (Recommended primary alert)
“💎 SmartSense: DIAMOND TIER (90+)”: Only alerts for the absolute highest-scoring signals.
“🔥 SmartSense: PLATINUM TIER (80-89)”: Alerts for strong signals.
“✨ SmartSense: GOLD TIER (70-79)”: Alerts for solid signals.
“⏳ SmartSense: Setup Building”: Early warning alert (corresponds to “BUILDING” status).
Specific Pattern Alerts (e.g., “🔄 SmartSense: DIVERGENCE DETECTED”, “💥 SmartSense: SQUEEZE BREAKOUT”, “📈 SmartSense: MTF BULLISH ALIGNMENT”): Alert only when a final signal occurs and that specific condition contributed significantly. Useful for specialized strategies.
Configure the alert options (e.g., “Once Per Bar Close”) and notification method (popup, email, etc.).
Click “Create.”
Use the Scan Sensor efficiently find moments of high technical confluence across various market conditions, signaling the best times to deploy your detailed analysis or scanning routines. Remember to always use its output as a starting point for deeper investigation, not as a standalone trading decision.
This guide focuses specifically on the Screenshot Analysis feature of the Chart Analyzer tool. Unlike the Live Analysis, this mode allows you to get an AI-powered analysis based on a static chart image you provide.
Screenshot Analysis is designed for quick insights based on a chart image you upload. It’s ideal when you want the AI’s perspective on a specific pattern, setup, or historical moment captured in an image.
When you submit a screenshot:
Image Upload: Your image is securely uploaded.
Context Extraction: The AI attempts to identify the symbol (if you didn’t provide one) and the timeframe directly from the image.
Persona Selection: Based on the detected timeframe, an appropriate AI Trading Persona (e.g., Scalper, Swing Mentor) is assigned.
Sentiment Fetch: It gathers current News Headlines and the Fear & Greed Index to provide market context at the time of analysis (not the time of the screenshot).
AI Visual Analysis: The AI analyzes the chart image visually, identifying patterns, key levels, and indicator readings as depicted in the static image.
Report Generation: It synthesizes its visual findings with the fetched sentiment data into a comprehensive report, similar in structure to the Live Analysis report but based solely on the image provided.
Key Difference: Screenshot analysis relies entirely on the visual information in the image and current sentiment data. It does not have access to live market data, order flow, precise volume confirmation, or deep historical data for backtesting like the Live Analysis tool does.
Navigate to the main analyzer and click on the “Screenshot” tab.
You have several ways to provide the image:
Click to Select: Click the designated upload area to open your file browser and select an image (.jpg, .png, .gif, .webp).
Drag & Drop: Drag an image file directly onto the upload area.
Paste: Copy an image (e.g., from your charting software or a website) and paste it directly onto the page (Ctrl+V or Cmd+V).
A preview of your uploaded image will appear.
File Requirements:
Type: JPG, PNG, GIF, WEBP
Size: Maximum 5MB (configurable by admin).
Enter the asset’s ticker (e.g., BTC, ETH).
Why it helps: If you provide the symbol, the AI can fetch relevant, up-to-the-minute news headlines and sentiment data specific to that asset, adding valuable context to the visual analysis. If you leave it blank, the AI will try to detect the symbol from the image, which might not always be accurate, and the news context will be more general.
You have two options:
Run Regular Analysis (1 Credit): Uses a faster, more cost-effective AI model. Good for quick checks and standard patterns.
Run Premium Analysis (2 Credits): Uses a more advanced, powerful AI model capable of deeper pattern recognition and more nuanced insights. Recommended for complex charts or critical setups.
Click the corresponding button. The analysis process will begin, typically taking 20-45 seconds.
The results panel is very similar to the Live Analysis, with a few key distinctions:
Provides the high-level takeaway:
Core Signal: BULLISH, BEARISH, NEUTRAL, NO TRADE (based only on the image).
Confidence Score: AI’s conviction (0-100%).
Trading Persona: The persona assigned based on the detected timeframe.
Asset Info: Shows the detected/entered Symbol and detected Timeframe. The Source will indicate “Screenshot”.
Trade Plan (Visual Estimate): Entry Zone, Stop-Loss, Targets – these are estimated by the AI based purely on the visual levels in the static image.
Key Levels (Visual Estimate): Support and Resistance identified visually.
Patterns Detected: Patterns visually identified by the AI in the image.
Summary: The AI’s one-paragraph thesis based on the image.
This section displays the exact screenshot image you uploaded. There is NO “Live Now” toggle because the analysis is based solely on this static image.
Toggles the detailed report sections, providing the evidence behind the summary.
The full report mirrors the Live Analysis structure but with important caveats:
Visual Analysis: Describes what the AI saw in your screenshot.
Technical Analysis: Discusses indicators (RSI, MACD, etc.) as they appear in the image. Mentions like Volume Profile POC or Fibonacci levels are visual estimates by the AI based on the image, not precise calculations.
Market Context: Includes the Fear & Greed Index and News Analysis fetched at the time you ran the analysis. It will state that Higher-Timeframe (HTF) context is unavailable from a static image.
Orderflow Analysis: This section will be absent or state N/A, as order book and trade data cannot be derived from a static image.
Risk Analysis:
Monte Carlo Simulation / VaR / CVaR: These metrics will be absent or state N/A as they require historical data not available from a screenshot.
Strategy Scorecard: Will state N/A as backtesting requires historical data.
The report may include a general risk warning based on the visible volatility in the screenshot.
This functions identically to the Live Analysis version:
Start Session (1 Credit): Unlocks a 3-question Q&A session.
Ask Questions: You can ask the Sensei to clarify aspects of the screenshot analysis report. Examples:
“Explain the ‘Rounding Bottom’ pattern you identified in the image.”
“Based on the image, why did you estimate support at that level?”
“What does the news sentiment you fetched imply for the pattern visible in the screenshot?”
Get Answers: Sensei responds based on the report generated from the image.
Restart (Optional): Purchase another 3 questions for 1 credit.
Quick Pattern Check: Saw an interesting pattern on a chart? Upload a screenshot for the AI’s quick take.
Historical Review: Have a screenshot of a past trade setup? Analyze it to see what the AI would have interpreted at that moment (keeping in mind news/sentiment will be current).
Learning: Upload charts with known patterns to see if the AI identifies them correctly and learn from its descriptions.
Sharing: Get a structured AI report based on a chart image you want to share or discuss.
Important Limitation: Remember that Screenshot Analysis is based on a single moment in time captured in an image. Market conditions, volume, and order flow can change rapidly. Always use it as a supplementary tool alongside live data and your own analysis.
Welcome to the most powerful tool in your analysis arsenal. This guide provides a comprehensive overview of the Live Market Analysis tool. Unlike the “Scan Sensor,” which rapidly scans many assets for a single signal, this tool performs a deep, multi-faceted AI analysis on a single asset you choose, acting as your personal AI research analyst.
The Live Market Analysis tool is your AI-powered co-pilot for deep-diving into any specific asset. When you request an analysis, you are commissioning a full-scale report. The tool initiates a complex backend process that mimics the workflow of a professional human analyst:
Data Curation: It gathers all relevant real-time market data, including OHLCV (candlestick) data, full order book depth, a log of recent trades, and the trend from higher timeframes.
Sentiment Analysis: It scans multiple global news feeds for relevant headlines, performs advanced sentiment analysis on them, and fetches the current Fear & Greed Index for a macro view.
Chart Generation: It creates a static snapshot of the chart, complete with key indicators and patterns, which serves as the “evidence” for the AI.
AI Analysis (The “Brain”): It feeds this chart image and all the collated data (Technicals, Orderflow, Sentiment, and Risk Metrics) to an advanced AI model. The model is primed with a specific “Persona” (e.g., “Scalper,” “Swing Trader”) based on your chosen timeframe.
Quantitative Risk Modeling: It runs a Monte Carlo simulation with 1000+ potential price paths to determine statistical risk factors like Value at Risk (VaR). It also backtests a suite of simple strategies on the asset’s recent history to see what’s been working.
Report Delivery: It parses the AI’s highly detailed report into the two-part interface you see: a clear, actionable summary panel and a full, in-depth multi-page report.
When you click “Run Live Analysis,” you aren’t just running a simple script. You are submitting a job to a dedicated processing queue.
Queueing: Your request is placed in a queue. The button will update to show its status (“Waiting in queue…”).
Processing: A dedicated worker picks up your job. It performs all the data gathering, AI analysis, and risk modeling steps described above. The button will show “Processing analysis…”. This entire process is resource-intensive and can take 30-60 seconds.
Completion: Once finished, the full analysis panel appears on your screen, and one credit is deducted from your account.
Navigate to the main analyzer and click on the “Live” tab to open the Live Analysis interface.
You will see four fields:
Exchange: Select the exchange where the asset is listed (e.g., BINANCE, COINBASE, KRAKEN_FUTURES).
Symbol: Enter the asset’s ticker (e.g., BTC, ETH, SOL).
Market: This is typically set to Crypto.
Timeframe: Select the chart timeframe you want to analyze (e.g., 15m, 1h, 4h, 1d).
As you change the timeframe, the AI Persona will update. This is critical.
⚡ Rapid-Fire Scalper (e.g., 1m, 5m): The AI focuses on immediate price action, order flow, and micro-patterns. Its report will be fast and tactical.
🧘 Patient Swing Mentor (e.g., 4h, 1d): The AI focuses on major market structure, weekly trends, and significant support/resistance zones. Its report will be strategic and patient.
Click the “Run Live Analysis” button. The button will update to show the status. A single analysis will deduct one credit from your account.
Once complete, the full analysis appears. It is designed in two layers: the “Summary” for a quick answer and the “Full Report” for deep evidence.
This is your high-level dashboard.
Core Signal: The AI’s overall bias: BULLISH, BEARISH, NEUTRAL, or NO TRADE. A “NO TRADE” signal is valuable—it means the AI sees no high-quality setup and recommends staying flat.
Confidence Score: A 0-100% score indicating the AI’s conviction in its signal. A BULLISH signal with 85% confidence is much stronger than one with 55%.
Trading Persona: Confirms the persona (e.g., “Intraday Strategist”) that performed the analysis.
Asset Info: Confirms the Symbol, Timeframe, and Exchange of the report.
Trade Plan:
Entry Zone: The AI’s suggested price range for entry.
Stop-Loss: A suggested price level for risk management.
Target 1 / Target 2: Suggested price targets.
Key Levels:
Support: The AI’s identified support level.
Resistance: The AI’s identified resistance level.
Patterns Detected: A list of all chart patterns the AI visually identified (e.g., “Bull Flag,” “Head and Shoulders”).
Summary: A short, one-paragraph thesis from the AI explaining its reasoning.
The Static Analysis Chart: Below the summary is a static (non-moving) chart. This is the exact chart image that the AI analyzed. It includes all the indicators and pattern lines the AI used, so you can see what it saw.
The “⚡ Live Now” Button: This is a powerful toggle. Clicking this button will replace the static analysis chart with a fully interactive, live TradingView widget. This allows you to:
See the AI’s analysis on the static chart.
Click “⚡ Live Now” to instantly see where the price has moved since the analysis was run.
Perform your own live analysis and chart interactions.
This button toggles the detailed, multi-panel report. This is where you find the deep data and evidence to back up the summary. It includes:
Visual Analysis: What the AI saw in the chart image (e.g., “Price is in a clear descending wedge,” “A bearish engulfing candle just formed”).
Technical Analysis: A breakdown of all key indicators (RSI, MACD, ADX, VWMA, Bollinger Bands) and chart structures (Volume Profile POC, Fibonacci Levels).
Market Context:
Higher-Timeframe (HTF): The trend bias from a higher timeframe (e.g., “The 4h chart is in a downtrend, so this 15m bounce is counter-trend”).
Sentiment: The current Fear & Greed Index score.
News Analysis: Key headlines, the overall news sentiment (e.g., 60% Positive / 40% Negative), and a flag if high-impact news was detected.
Orderflow Analysis (Crypto): A powerful view into the market’s “engine.”
Orderbook: The current Bid/Ask Ratio (e.g., “1.5 Bids for every 1 Ask” is bullish). It also detects large “Buy Walls” or “Sell Walls” that could act as support/resistance.
Taker Aggression: An analysis of recent trades to see if aggressive buyers (lifting the ask) or sellers (hitting the bid) are in control.
Risk Analysis: This is your quantitative risk assessment.
Monte Carlo Simulation: The results of 1000+ price simulations.
95% VaR (Value at Risk): The maximum expected loss 95% of the time over the next period (e.g., “A 3.5% VaR means there is a 95% chance you will not lose more than 3.5%”).
95% CVaR (Conditional VaR): Even more important. This is the average loss you can expect if the VaR threshold is breached (e.g., “A 5% CVaR means that in the worst 5% of cases, the average loss was 5%”).
Strategy Scorecard: The results of backtesting simple strategies (like RSI Mean Reversion) on this asset’s recent history, showing you what type of trading has been working (e.g., “Momentum strategies are failing, but mean-reversion is profitable”).
After a summary and report are generated, a new panel appears at the bottom labeled “Ask Sensei”. This is a powerful, interactive feature.
What it is: A chat interface that allows you to ask clarifying questions about the specific report you just ran. The AI (Sensei) has the full report as its context.
How it Works:
Start Session: Click the “Ask Sensei (1 Credit / 3 Qs)” button. This will deduct one credit and open the Q&A panel.
Ask Questions: You get 3 questions per session. You can ask things like:
“Can you explain the ‘Bearish Divergence’ you mentioned in more detail?”
“Why is the ‘Taker Aggression’ considered bearish?”
“What is the most important factor leading to the ‘NO TRADE’ signal?”
Get Answers: The Sensei will provide a direct answer based on the report’s content.
Restart (Optional): Once you use your 3 questions, the session ends. You can choose to start a new session by clicking “Ask 3 More Questions (1 Credit)” to continue digging deeper.
Use Case 1: The “Second Opinion”
Scenario: You’ve done your own analysis and think SOL looks bullish on the 1h chart.
Action: Run a SOL 1h “Live Analysis.”
Result: The AI report comes back BEARISH with 75% confidence. You use an “Ask Sensei” question: “Why are you bearish?” The Sensei replies, “The analysis is bearish due to a strong bearish divergence on the 4h (HTF) context and a large ‘Sell Wall’ detected at $150, which you can see in the ‘Orderflow Analysis’ section.” You now have new, actionable data you missed.
Use Case 2: The “Scanner Deep Dive”
Scenario: The “Scan Sensor” or “Catalyst” tool fires a 💎 DIAMOND signal for AVAX on the 15m chart.
Action: You immediately go to the “Live Analysis” tab and run an AVAX 15m report.
Result: The full report shows a 90% confidence BULLISH signal. The “Risk Analysis” shows a low VaR, and the “Orderflow” panel confirms aggressive buyers. This gives you the full picture to act on the scanner’s signal.
Use Case 3: The “Risk Assessment”
Scenario: You want to trade DOGE but know it’s extremely volatile.
Action: Run a “Live Analysis” on DOGE.
Result: The report’s “Risk Analysis” section shows a 95% VaR of 12%. This tells you that a 12% loss is statistically within the normal range of outcomes, so you can adjust your position size accordingly or decide it’s too risky for you.
Use Case 4: The “Strategy Check”
Scenario: The market feels choppy, and your breakout strategy keeps failing.
Action: Run a “Live Analysis” on ETH.
Result: You check the “Strategy Scorecard” in the full report. It shows that “Momentum” and “Breakout” strategies have a 20% win rate, while “RSI Mean Reversion” has a 70% win rate. This gives you the data to adapt your personal strategy to the current market regime.
Welcome to MetaScan, your portal into an immersive, 3D chart metaverse experience. This guide covers everything you need to know about navigating and utilizing this unique analysis environment.
MetaScan transforms traditional 2D chart analysis into a fully interactive 3D/VR environment built using Babylon.js. Instead of looking at a chart, you step inside it.
When you launch MetaScan:
Data Fetch: The system retrieves historical OHLCV data, calculated technical indicators, and current market sentiment (News + Fear & Greed) for your chosen asset and timeframe.
Scene Generation: A dynamic 3D scene is constructed:
Price action is rendered as 3D candlestick and volume bars.
Key indicators like EMAs and Bollinger Bands become 3D lines floating alongside the price.
Volume and RSI are displayed in separate panes below the main price chart.
Market sentiment is visualized as a dynamic particle field (“Sentiment Scape”).
Potential future price paths (based on Monte Carlo simulations) are shown as translucent “Ghost Candles.”
Immersive Experience: You are placed within this 3D environment with intuitive controls for navigation and interaction.
Select the “MetaScan” Tab: In the main Chart Analyzer interface, click the “MetaScan” tab.
Enter Asset Details:
Exchange: Choose the exchange (e.g., BINANCE, COINBASE).
Symbol: Enter the asset ticker (e.g., BTC, ETH).
Market: Typically Crypto.
Timeframe: Select the desired timeframe (e.g., 1h, 4h, 1d).
Click “Enter MetaScan”: This initiates the data fetching and scene generation process. It costs 1 credit per session. The button text will update to show progress (“Initializing…”, “Fetching Data…”, “Creating Scene…”).
Once the scene loads, you’ll find yourself inside the 3D chart.
Look Around: Click and drag your mouse.
Zoom: Use your mouse scroll wheel.
Pan Chart Sideways: Hold CTRL and press the Left or Right Arrow keys.
Exit MetaScan: Press the ESC key.
A brief Welcome Panel appears initially explaining these basic controls. You can dismiss it by clicking anywhere.
3D Candlesticks & Volume Bars: The core price and volume data rendered in three dimensions. Green for up candles/volume, Red for down.
Indicator Ribbons/Lines:
EMA 20 (Orange): Floating ribbon representing the 20-period Exponential Moving Average.
EMA 50 (Blue): Floating ribbon representing the 50-period Exponential Moving Average.
Bollinger Bands (Grey): Upper, middle, and lower bands visualized as ribbons.
RSI Pane (Purple Line): A separate pane below the volume bars showing the Relative Strength Index as a 3D line.
Sentiment Scape (Particles): A field of flowing particles below the chart floor, visualizing market sentiment (explained below).
Ghost Candles (Translucent): Semi-transparent candles extending from the last real candle, showing potential future price paths based on Monte Carlo simulations.
Axis Labels & Grid: Price labels appear on the sides, Time/Date labels appear below the price pane, providing spatial context. Vertical lines often mark the start of new days (UTC).
Starfield Background: A subtle cosmic background enhances the immersive feel.
Grid Floor: A grid pattern helps with spatial orientation.
Top-Left Panel:
Logo & Asset Info: Displays the ChartSense AI logo and the Symbol - Timeframe you are viewing.
🧠 Ask Sensei Button: Triggers an AI analysis of the currently viewed chart section (explained below).
Hover Tooltips: Pointing your mouse cursor at a candlestick body, wick, or volume bar will highlight it and display a tooltip showing:
Date & Time (UTC)
Open, High, Low, Close prices
Volume (for volume bars)
Dynamic Price Label: A yellow label follows the closing price of the currently focused candle (controlled by the scrubber), making it easy to see the exact price.
Temporal Scrubber (Bottom Center):
A slider that lets you “travel” through the chart’s history.
Moving the slider updates which candles are displayed and recalculates indicators based on the visible data range.
The label above shows the date and candle number corresponding to the slider’s position.
Indicator Toggles (Bottom Right): Checkboxes allow you to show or hide:
EMA 20
EMA 50
RSI
Bollinger Bands
Ghost Candles
Help Button (?) (Top Right): Opens a fullscreen panel explaining controls and features. Click the ‘X’ or anywhere outside the panel to close it.
This dynamic particle field below the chart is a unique visualization of overall market mood:
Composite Score: It blends the general market’s Fear & Greed Index (60% weight) with the asset-specific News Sentiment (40% weight).
Color: Indicates the dominant emotion:
Red (Fear): Score below 45. Deeper red for Extreme Fear (below 25).
Blue (Neutral): Score between 45 and 55.
Green (Greed): Score above 55. Brighter green for Extreme Greed (above 75).
Turbulence: The intensity of particle movement reflects volatility associated with the sentiment. Fear often brings higher turbulence.
✨ Catalyst Sparkle Effect: If the system detects strong news sentiment (e.g., >70% positive or negative headlines specifically for this asset), subtle golden sparkles appear within the Sentiment Scape, highlighting a potential news-driven catalyst.
This slider is more than just a timeline. As you move it:
The chart dynamically renders candles up to the selected point in history.
Indicators (EMAs, Bollinger Bands, RSI) are recalculated based on the data visible up to that point, allowing you to see how signals evolved over time.
It provides a powerful way to review past price action and indicator behavior in an immersive context.
Clicking this button triggers a contextual AI analysis:
Context: It analyzes a slice of ~50 candles ending at the current position of the Temporal Scrubber.
Question: It asks the AI a pre-defined question: “What is the most important pattern or signal in this section?”
Response: A panel appears displaying the AI’s concise (1-2 sentence) insight based only on that specific chart segment.
Usage: Ideal for getting quick AI feedback on patterns or conditions at specific historical points you navigate to using the scrubber.
Note: This is a separate, single-shot analysis function, distinct from the multi-question “Ask Sensei” Q&A panel available after a full Live or Screenshot analysis. It does not cost additional credits beyond the initial MetaScan session entry.
When the Temporal Scrubber is at the end (showing the most recent data), translucent “Ghost Candles” appear.
These represent a sample of potential future price paths generated by the Monte Carlo simulation (also used in the Live Analysis Risk section).
Their overall color (bullish green, bearish red, or neutral grey) indicates the average simulated outcome.
They provide a visual glimpse into the statistical possibilities based on historical volatility and drift, adjusted by the AI’s directional bias.
Immersive Pattern Recognition: Spotting trends, channels, wedges, and other patterns can be more intuitive in a 3D space.
Sentiment Visualization: Quickly grasp the alignment (or divergence) between price action and the underlying market mood via the Sentiment Scape.
Historical Review: Use the Temporal Scrubber to intuitively replay market movements and indicator signals.
Contextual AI Insights: Get rapid AI feedback on specific chart sections using the integrated Ask Sensei feature.
Engaging Analysis: Offers a more dynamic and engaging way to interact with chart data compared to traditional 2D charts.
MetaScan is built using the Babylon.js 3D engine.
Requires a modern web browser with WebGL support (Chrome, Firefox, Edge recommended). Performance may vary based on your hardware.
While usable on desktops, it’s designed with VR compatibility in mind (requires a WebXR-compatible browser and VR headset for the full VR experience).
Mobile devices are generally not supported due to performance limitations and control scheme differences.
Step inside your charts and explore the market from a new dimension with MetaScan! Remember to use the Help (?) button within the scene for quick control reminders.
Welcome to the Catalyst Scanner, a powerful tool designed to quickly identify assets poised for potentially significant price movements. This guide covers how it works, how to use it effectively, and how to interpret its results.
The Catalyst Scanner is your proactive market screening tool. Instead of performing deep analysis on one asset like the “Live Analysis” tool, the Catalyst Scanner rapidly evaluates a watchlist of assets you define, searching for specific conditions that often precede volatility expansion or trend initiation. Its goal is to highlight assets showing signs of “coiling energy” or being influenced by strong news catalysts.
When you initiate a Catalyst Scan:
Watchlist Processing: The system iterates through each symbol in your saved watchlist.
Data Fetching (Per Symbol): For each symbol, it retrieves historical OHLCV data for your selected timeframe (e.g., 4h) and potentially a higher timeframe (e.g., 1d) for context. It also fetches relevant news headlines.
Core Indicator Calculation (Per Symbol): It calculates key metrics:
Volatility Compression: Using Bollinger Bandwidth to measure how tightly price is consolidating. Extreme tightness often precedes expansion.
Volume Analysis: Comparing recent volume to historical averages. Low volume during consolidation (“volume dry-up”) can signal accumulation before a move.
Momentum Divergence: Checking for discrepancies between price action and indicators like RSI and MACD, which can signal reversals.
On-Balance Volume (OBV): Tracking volume flow to detect potential accumulation or distribution not obvious from price alone.
News Sentiment: Analyzing recent headlines for strongly positive or negative sentiment.
Market Regime: Determining if the asset is currently Trending or Ranging.
Pattern Apex Detection: Identifies if price is nearing the apex (convergence point) of a detected chart pattern (like a triangle or wedge), a common breakout zone.
Multi-Timeframe (MTF) Context: Checks if volatility is also compressing on a higher timeframe, adding confluence.
Catalyst Score Calculation (Per Symbol): A proprietary algorithm calculates a “Catalyst Score” (0-100) based on the factors above.
Dynamic Weighting: The importance of each factor (e.g., volatility vs. divergence) is adjusted based on the detected Market Regime. Ranging markets give more weight to volatility compression, while trending markets give more weight to divergence and OBV.
High Scores Indicate: Extreme volatility contraction, significant volume dry-up, strong divergence, clear OBV accumulation/distribution, strong news sentiment, approaching pattern apex, or MTF volatility squeeze.
Reason Generation: Based on the highest contributing factors, a concise “Reason” is generated explaining why the asset received its score.
Results Aggregation: All scored assets are collected and sorted, with the highest scores presented first.
Click the “Catalyst” tab in the main Chart Analyzer interface.
This is the core of the Catalyst Scanner. Use the input field to add symbols:
Type a Symbol: Enter a ticker (e.g., BTC, ETH) and press Enter or Space.
Tags: Each symbol appears as a tag.
Remove: Click the × on a tag to remove it.
Count: The number of symbols is displayed.
Save: Click the “Save Watchlist” button to store your current list for future use. Your saved list loads automatically when you open the Catalyst tab.
Exchange: Choose the exchange your watchlist symbols trade on.
Timeframe: Select the timeframe you want to scan (e.g., 1h, 4h, 1d). Lower timeframes detect short-term catalysts, higher timeframes detect larger potential moves.
Credit Cost: The scan costs 1 credit per symbol in your watchlist. A confirmation prompt will appear showing the total cost.
Click “Scan My Watchlist”: If you confirm, the scan begins. The button shows progress (“Scanning…”).
Once the scan completes, the results are displayed below, along with view toggle buttons.
List View (Default): Shows results as a detailed list.
Heatmap View: Shows results as a color-coded grid for quick visual assessment.
Each item in the list represents a symbol from your watchlist:
Symbol: The asset ticker (e.g., SOL/USDT).
Catalyst Score Bar: A visual representation of the score (0-100%).
Color: Green (High Score > 75), Yellow (Medium Score 60-75), Red (Low Score < 60).
Value: The numerical score percentage.
Reason: The concise explanation for the score (e.g., “Extreme volatility contraction detected,” “Strong bullish divergence found”).
⚡ News Snippet: If a relevant, recent news headline contributed significantly to the score, it’s displayed here.
Analyze Chart Button: Click this button to instantly switch to the “Live Analysis” tab, pre-filled with this symbol and the scanned timeframe, allowing you to perform a deep-dive analysis.
This view provides a quick visual overview of your watchlist scores:
Boxes: Each symbol is represented by a box.
Color: Indicates the score range (Red = Low, Yellow = Medium, Green = High).
Content: Shows the symbol ticker and its numerical score.
Tooltip: Hovering over a box reveals the “Reason” for its score.
Click Action: Clicking any box also switches you to the “Live Analysis” tab for that symbol and timeframe.
A high Catalyst Score (> 75) suggests an asset is exhibiting multiple conditions often preceding significant price moves. Key factors that boost the score include:
Volatility Compression: Bollinger Bands tightening significantly (low bandwidth %).
Volume Dry-Up: Recent volume dropping well below the historical average during consolidation.
Divergence: Price making new highs/lows while momentum indicators (RSI, MACD) fail to confirm.
OBV Trend: OBV showing strong accumulation (rising while price is flat/down) or distribution (falling while price is flat/up).
Strong News Sentiment: A high percentage (>60-70%) of recent news being strongly positive or negative.
Apex Proximity: Price consolidating near the tip of a visually identified Triangle or Wedge pattern.
MTF Squeeze: Volatility compression occurring simultaneously on the scanned timeframe AND a higher timeframe.
The “Reason” highlights the primary factor driving a high score.
The Catalyst Scanner is best used as a starting point, not a trading signal generator.
Workflow:
Maintain a watchlist of assets you are interested in.
Run the Catalyst Scanner periodically (e.g., daily on the 4h timeframe).
Focus on the top 1-3 assets with the highest scores (ideally > 75) and compelling “Reasons”.
Click “Analyze Chart” for those high-scoring assets.
Perform a full “Live Analysis” to get the complete picture (AI thesis, trade plan, risk metrics, order flow).
Make your trading decision based on the combination of the Catalyst alert and the detailed Live Analysis report.
Example: The Catalyst Scanner shows ADA with a score of 88%, Reason: “Extreme volatility contraction detected. Price nearing apex of Symmetrical Triangle.” You click “Analyze Chart,” run the Live Analysis, and the full report confirms a high-confidence breakout setup with good risk metrics. This provides a much stronger basis for a trade than the Catalyst score alone.
Use the Catalyst Scanner to efficiently monitor your universe of assets and pinpoint those most likely to offer trading opportunities soon.
Welcome to the Market Conviction analysis tool. This feature provides a high-level, synthesized view of the overall cryptocurrency market sentiment and underlying strength by blending news narratives with on-chain data. This guide explains how it works, how to use it, and how to interpret its unique report.
Market Conviction analysis aims to answer the question: “What’s really happening in the crypto market right now?” It goes beyond individual charts to gauge the overall health, sentiment, and potential direction of the market by comparing:
Off-Chain Data (The News Story): What narratives are driving headlines? What is the general market mood (Fear & Greed)?
On-Chain Data (The Real Story): What does the underlying blockchain activity show? Are people actually using the networks? Is capital flowing in or out?
By synthesizing these data streams with AI, it generates a “Conviction Score” and a detailed briefing to help you understand if the news hype aligns with fundamental network activity.
When you request a Market Conviction analysis:
Data Fetching: The system gathers real-time data from multiple sources:
On-Chain Metrics: Total Crypto Market Cap, Bitcoin Dominance, Bitcoin Transaction Count (24h), Ethereum Gas Price (Gwei).
Off-Chain Sentiment: Fear & Greed Index value and classification.
News Aggregation: Recent headlines related to Bitcoin (as a market proxy) and major financial events.
Data Synthesis Prompt: All collected data is structured into a specialized prompt (_build_conviction_prompt) designed to guide the AI.
AI Analysis: The prompt and data are sent to an AI model (gpt-5-mini) for analysis and synthesis. The AI is instructed to compare the “news story” with the “real story” (on-chain data) and follow a strict output format.
Report Generation: The AI generates a structured report containing the Conviction Score, Market State, and detailed Analyst Briefing sections.
Select the “Conviction” Tab: Navigate to the main analyzer interface and click on the “Conviction” tab.
Click “Analyze Market Conviction”: This button initiates the analysis.
Credit Cost: This analysis costs 1 credit.
Process: The button will show a loading state (“Synthesizing Conviction…”) while the data is fetched and analyzed by the AI (typically takes 15-30 seconds).
View Results: The analysis report will appear in the main content area once complete.
The report is designed to be clear, concise, and easy to understand, avoiding excessive jargon.
Conviction Score (0-100): A numerical representation of the overall market conviction. Higher scores indicate stronger alignment between positive sentiment, news, and on-chain activity (or strong alignment towards a sell-off). Lower scores indicate divergence or uncertainty.
Gauge Visualization: A semi-circle gauge provides an immediate visual sense of the score.
Market State: A label describing the current condition based on the score and underlying data analysis. Possible states:
High Conviction Rally: Strong alignment of positive factors.
High Conviction Sell-Off: Strong alignment of negative factors.
Divergence - Potential Bull Trap: Positive news/sentiment but weak on-chain data.
Divergence - Potential Bear Trap: Negative news/sentiment but strong on-chain data.
Low-Conviction Chop: Mixed signals, uncertainty, likely range-bound activity.
This is the core narrative generated by the AI, broken down into specific insights:
🧠 Dominant Narrative: A single sentence summarizing the main story being told by the news headlines (e.g., “News focuses on regulatory concerns, suggesting a cautious market.”).
🧠 Sentiment Alignment: Explains whether the Fear & Greed Index matches the dominant news narrative (e.g., “Yes, the ‘Fear’ reading aligns with the negative headlines, indicating market participants are reacting to the news.”).
🧠 Most Impactful Headline: Identifies the single most important news item currently influencing the market and explains why in simple terms.
🧠 Comprehensive Synthesis & Strategic Outlook:
The Main Takeaway: The single most crucial point derived from comparing news and on-chain data (e.g., “Despite fearful headlines, on-chain transaction counts remain high, suggesting underlying network usage is resilient.”).
The News Story vs. The Real Story: Directly contrasts the off-chain narrative with the on-chain reality, pointing out convergences or divergences (e.g., “While news talks of price drops, Bitcoin dominance is rising, showing capital might be flowing into BTC as a ‘safe haven’ within crypto.”).
What to Watch Out For: Simple, actionable advice based on the synthesis. It highlights key data points (e.g., ETH gas price, BTC dominance) to monitor for confirmation or change in the market state.
🧠 Simple Advice: Tailored guidance for different participant types:
If you’re new: Basic, cautious advice relevant to the current state.
If you trade: Advice focused on short-term implications (e.g., “Expect volatility, look for confirmation before entering trades.”).
If you invest long-term: Advice focused on the bigger picture (e.g., “Focus on underlying network growth despite short-term news noise.”).
🧠 Bottom Line: A final, one-sentence summary encapsulating the entire analysis.
Macro Context: Get a quick understanding of the overall market environment before analyzing individual assets. Is it a “risk-on” or “risk-off” day?
Narrative Check: See if the prevailing news stories match the actual on-chain activity. Is the hype real, or is it a potential trap?
Regime Identification: Understand the current Market State to tailor your trading approach (e.g., trend-following in high conviction, range-trading in chop).
Complementary Tool: Use the Market Conviction analysis alongside individual Live or Screenshot analyses for a more holistic view. For example, if Market Conviction shows a “Potential Bear Trap” (fearful news, strong on-chain), a bullish setup on an individual chart might have a higher probability of success.
Use the Market Conviction analysis to cut through the noise and gain a clearer perspective on the fundamental drivers and sentiment shaping the cryptocurrency market.
Welcome to the AI Trading Psychologist, your personal performance coach designed to analyze your trading behavior and provide actionable insights. This guide explains its purpose, how it works, how to use it, and how to interpret its detailed report.
The Trading Psychologist goes beyond technical chart analysis to focus on you, the trader. Its goal is to identify behavioral patterns, psychological biases (like FOMO or revenge trading), and decision-making habits that might be impacting your trading results. By analyzing your actual trade history, it provides a data-driven diagnosis and a personalized coaching plan to help you improve consistency and mindset.
When you initiate a Trading Psychologist analysis:
Input Method Selection: You choose how to provide your trade history:
CSV Upload: Uploading a standard comma-separated value file containing your trades.
Paste Text: Pasting trade history directly into a text area.
Screenshot Upload: Uploading an image of your trading platform’s history log.
Data Extraction & Parsing:
CSV/Paste: The system intelligently parses the text, identifying header rows and relevant columns (like Time, Symbol) even if they have different names (e.g., ‘Date’, ‘Pair’, ‘Time (UTC)’).
Screenshot: An AI model performs Optical Character Recognition (OCR) to extract trade details (Time, Symbol) from the image into a structured format.
Market Context Fetching: For a subset of the most recent trades identified (up to 25), the system fetches historical market data (using CoinAPI) for a 10-minute window around each trade. This helps understand the market conditions (e.g., volatility, trend) when those specific trades were executed.
AI Prompt Generation: A specialized, detailed prompt (build_psychologist_prompt or build_psychologist_prompt_for_screenshot) is constructed. This includes:
The raw or extracted trade history.
The fetched market context snippets.
Specific instructions for the AI to act as a trading psychologist, analyze the data for behavioral patterns, and structure the output strictly according to predefined sections.
AI Behavioral Analysis: The prompt and data are sent to an AI model (gpt-5-mini) for analysis. The AI synthesizes the trade history and market context to infer psychological drivers and performance patterns.
Report Generation: The AI generates a structured report in Markdown format, following the specific sections outlined in the prompt.
Select the “Psychologist” Tab: Navigate to the main analyzer interface and click the “Psychologist” tab.
Choose Input Source: Select one of the radio buttons:
Upload CSV File
Upload Screenshot
Paste Trade History
Provide Trade History:
CSV: Click the upload area or drag-and-drop your .csv file.
Screenshot: Click the upload area or drag-and-drop your image file (.jpg, .png, .gif, .webp). Ensure the image clearly shows trade details like symbol, time/date, and ideally entry/exit prices or P&L.
Paste: Copy your trade history text (e.g., from an exchange report or spreadsheet) and paste it into the provided text area.
Run Analysis:
Click “Run Behavioral Analysis”: This initiates the process.
Credit Cost: This analysis costs 10 credits. Ensure you have sufficient credits.
Process: The button will show a loading state (“Analyzing…”) while the data is processed, market context is fetched (this can take a moment), and the AI generates the report.
View Results: The full Trading Psychologist report will appear in the main content area once complete.
The report is structured into specific sections designed to provide a clear diagnosis and actionable plan. It uses an empathetic yet direct coaching tone.
🎭 Your Trading Archetype: A creative label summarizing the dominant behavioral pattern observed (e.g., “The Overconfident Scalper,” “The Hesitant Investor,” “The Impulsive Scalper”).
📊 Data-Driven Diagnosis: A bulleted list (usually 3+ points) identifying specific trading issues backed by evidence from the provided history. It often connects patterns to the market context (e.g., “Aggressive entries observed during high volatility periods, suggesting attempts to catch falling knives.”).
🌎 Market Conditions Analysis: Describes the market environment (trending, ranging, volatile) during the analyzed trades, based on the fetched context data. It assesses if your actions were generally aligned with or fighting against the prevailing short-term market conditions. (If context couldn’t be fetched or wasn’t provided, it will state so).
🧠 Psychological Drivers: Infers the likely mindset behind the diagnosed behaviors, choosing from common biases like:
FOMO (Fear Of Missing Out): Entering trades late or chasing pumps.
Revenge Trading: Increasing risk after losses to “win back” money quickly.
Impatience: Forcing trades when no clear setup exists.
Lack of Confidence: Exiting winning trades too early or hesitating on valid entries.
✅ Key Strengths: Highlights 1-2 positive aspects observed in the trading history (e.g., “Demonstrates ability to identify potential support levels,” “Shows discipline in cutting some losing trades quickly.”). This provides encouragement and acknowledges what’s working.
🚀 Actionable Coaching Plan: Provides exactly 3 concrete steps to address the diagnosed issues. Each step includes:
The Action: What specific change to implement (e.g., “Implement a strict 1% risk per trade rule.”).
The ‘Why’: The reason this action will help (e.g., “To prevent large drawdowns from single losing trades.”).
Mindset Focus: The psychological shift needed to support the action (e.g., “Shift focus from ‘winning back losses’ to ‘preserving capital’.”).
Provide Sufficient Data: The more trade history you provide (ideally 50+ trades), the more accurate the analysis will be.
Use Clear Data:
CSV/Paste: Ensure the data has clear headers (like ‘Time’, ‘Symbol’, ‘Date’) and consistent formatting. The system is designed to be flexible but works best with standard formats.
Screenshot: Use clear, high-resolution screenshots where the text is easily readable. Avoid cropping out important columns like time/date or symbol.
Focus on Recent History: Analyzing your most recent trades (last few weeks or months) provides insights relevant to your current habits.
Review Regularly: Use the Trading Psychologist periodically (e.g., monthly) to track your progress and identify recurring patterns.
Use the AI Trading Psychologist as your objective performance coach to uncover hidden behavioral patterns and build a more disciplined, consistent approach to trading.
