INVITE-ONLY SCRIPT
Updated Edge Consistency Gauge [AGPro Series]
Edge Consistency Gauge [AGPro Series]
🧠 Core Idea
Two edges with the identical expectancy can feel completely different to trade. Does your edge grind out steady results, or does it lurch between rare big wins and long strings of losses?
📌 Overview / What it does
Edge Consistency Gauge measures the dispersion of a trading edge's per-trade outcomes — not price volatility, but the variability of the results themselves. From a measured win rate and payoff ratio it derives the outcome standard deviation, a per-trade consistency ratio, the realistic ±1σ swing band around the expectancy, and a 0-100 consistency score.
The score feeds a position-sizing decision layer: a suggested size percentage, the score needed to reach full size, and a stand-down rule for when the edge turns negative. The signature visual renders this directly on the price scale — two outcome bars sized in real ATR-based risk units, anchored at the latest close, with the expectancy and its ±1σ swing drawn as a band between them.
It does NOT predict price direction, generate entries, or guarantee outcomes. It measures how bumpy the ride is likely to be for a given edge, and translates that into a concrete sizing decision.
🎯 Purpose & Design Philosophy
Most traders judge an edge by its average outcome alone. Two setups with the same expectancy can carry very different practical risk: one produces a narrow, predictable spread of results, while the other produces a wide spread dominated by a few large outcomes. Sizing both the same way ignores that difference.
Edge Consistency Gauge was built to make that difference visible and actionable. It supports a risk-aware, evidence-based approach to position sizing — reducing size when results are dispersed and lumpy, and allowing full size only once an edge has demonstrated real consistency.
⚡ Why This Script Is Different
Most edge- and win-rate-focused tools stop at a single expectancy number, treating a smooth edge and a lumpy edge the same as long as the average is positive.
This script does NOT treat expectancy as the whole picture, and it does NOT recommend a fixed position size regardless of how dispersed the outcomes are.
Instead, it quantifies the spread around the expectancy, scores how consistent that spread is, and ties the score directly to a sizing recommendation — full size only when the edge is demonstrably smooth, reduced size when it is choppy or lumpy, and a stand-down flag when the edge turns negative.
⚙️ Methodology
1. Measured Samples
A transparent proxy trigger — price crossing a configurable EMA — opens a simulated trade with a stop at one ATR and a target at a configurable payoff multiple (R). Whichever level is reached first resolves the trade as a win or a loss.
2. Outcome Distribution
Wins and losses form a two-point outcome distribution. From the measured win rate and payoff R, the tool derives the expectancy (mean), the outcome standard deviation (σ), and the realistic ±1σ swing band in R.
3. Consistency Score
A per-trade consistency ratio (mean ÷ σ) is mapped to a 0-100 score, with adjustable sensitivity.
4. Decision Layer
The score is mapped to a suggested position size: full size above a configurable threshold, reduced size in two lower tiers, and a stand-down (0%) rule whenever expectancy turns negative.
🗺️ How to Read the Chart
• Entry / 0R line — a short reference line and tag marking the last close, the zero point outcomes are measured from.
• Loss bar — extends down to −1R, the fixed risk unit.
• Win bar — extends up to the current payoff R.
• Shaded band — the realistic ±1σ swing around expectancy, drawn between the bars.
• Dashed line — the expectancy (average outcome) itself.
• Win / loss markers — in Measured mode, small triangles flag the resolution of each proxy trade through history.
• Decision panel — lists every metric plus the current sizing recommendation.
🚦 Signals & States
• Smooth edge → high consistency score; outcomes cluster tightly around expectancy; full size supported.
• Choppy edge → positive but dispersed; reduced size recommended.
• Lumpy edge → positive but heavily uneven; further reduced size recommended.
• Negative edge → expectancy is at or below zero; stand-down, no size recommended.
States describe the shape of the outcome distribution, not a prediction about the next trade.
🔔 Alerts Logic
This version does not include alert conditions; consistency and sizing are read from the panel and chart in real time.
🧩 Confluence Logic
Confidence in the sizing recommendation is strongest when several conditions align: a healthy sample count behind the measured win rate, a consistency score well clear of the reduced-size thresholds, and an expectancy comfortably above zero. A single strong reading on a small sample is a hypothesis, not confluence.
📊 When to Use
• Deciding how much size an already-positive edge deserves.
• Comparing how evenly or unevenly the same trigger performs across instruments and timeframes.
• Building intuition for how outcome dispersion affects the practical experience of trading an edge.
• Teaching or studying the difference between expectancy and consistency.
⚠️ When NOT to Use
• On very small samples, where the measured win rate and consistency score are not yet reliable.
• In thin, illiquid markets where the ATR-based proxy stop and target resolve erratically.
• During extreme volatility, where realized outcomes diverge sharply from the ATR risk unit.
• As a market-timing or entry tool — it evaluates outcome dispersion, not the next move.
🎛️ Key Inputs
• Win-rate source — Measured (trigger + proof engine) or Manual.
• Payoff R — the reward-to-risk that defines the win outcome.
• Trigger EMA / ATR length / Max bars in trade — shape and resolve the proxy trades.
• Proof-engine lookback — optionally limits how far back trades are simulated, for faster loading and a more recent read.
• Consistency ratio scale — calibrates how the mean/σ ratio maps to the 0-100 score.
• Position sizing thresholds — full-size and reduced-size score thresholds, and the size percentage for each tier.
• Outcome bars — show/hide, distance from the last bar, width, and vertical scale.
• Panel — show/hide, position, theme (Dark/Light), and font size.
🖥️ Interface & Visual Design
The interface separates the analytical layers cleanly: a compact decision panel for the full metric set and sizing recommendation, and a native price-scale outcome-bar pair for the at-a-glance read on the chart itself. A merged header, a fixed professional palette, and luminance-aware text keep every element legible on dark and light charts. Scores are shown numerically, never as bars.
🧪 Practical Usage Workflow
1. Read the panel — note win rate, expectancy, outcome σ, and consistency score.
2. Read the bars — see the win/loss outcomes and the ±1σ band around expectancy directly in price terms.
3. Check the verdict — Smooth, Choppy, Lumpy, or Negative.
4. Apply the suggested size — or compare it against your own sizing rules.
5. Reassess as the sample grows — consistency can improve or degrade as more trades resolve.
🔍 Interpretation Guidelines
Treat expectancy and consistency as two separate questions. A positive expectancy tells you an edge should work over time; consistency tells you how smooth or rough that path is likely to be. A high consistency score does not guarantee the next trade wins — it describes the shape of the distribution the edge has produced so far, which can and does shift as conditions change.
🚫 What This Script Is NOT
• It is NOT a prediction engine — it does not forecast price or the next trade.
• It is NOT financial advice.
• It is NOT an automated or signal-trading system.
• It does NOT guarantee any win rate, payoff, or outcome.
⚠️ Limitations & Transparency
The measured win rate depends entirely on the built-in proxy trigger, which is a stand-in for real entries and will differ from them. The outcome distribution assumes a fixed payoff R and independent trades; real trading results cluster and edges drift over time. Timeframe, volatility, and liquidity all change how the proxy trades resolve. Past consistency is not future consistency.
🧠 Market Context Notes
Outcome dispersion is a property of a process across many trades, not of any single position. Regime shifts, volatility, and liquidity all change how proxy trades resolve, which moves both the expectancy and the spread around it. Read the consistency score as a snapshot of the current sample, refreshed as conditions and trade count evolve.
🧾 Use Case Examples
• A setup shows a 69% win rate at 2.0R with a tight ±1σ swing — the consistency score reads high and the panel recommends full size.
• A setup shows a 37% win rate at 2.0R with a wide ±1σ swing dominated by occasional large wins — the consistency score reads low despite positive expectancy, and the panel recommends reduced size.
🧱 System Philosophy
AGPro tools are built to support decisions, not replace them. Edge Consistency Gauge follows that principle: it exposes the shape of an edge's outcomes transparently, ties that shape to a concrete sizing recommendation, and leaves the final decision — and the responsibility — with the trader.
🔐 Non-Promise Statement
This script makes no promises and offers no certainty. It is a statistical and visualization tool. A high consistency score describes a sample, not a guarantee of future profit.
📉 Risk Disclosure
Trading involves substantial risk of loss and is not suitable for everyone. This script is provided for educational and analytical purposes only and does not constitute financial advice or a recommendation to buy or sell any instrument. All trading decisions, and their consequences, remain entirely your own responsibility.
📚 Educational Note
Use Edge Consistency Gauge to build intuition for the difference between an edge's average outcome and its practical ride. The most valuable takeaway is not any single reading, but the habit of sizing in proportion to how consistent an edge has actually shown itself to be.
🧠 Core Idea
Two edges with the identical expectancy can feel completely different to trade. Does your edge grind out steady results, or does it lurch between rare big wins and long strings of losses?
📌 Overview / What it does
Edge Consistency Gauge measures the dispersion of a trading edge's per-trade outcomes — not price volatility, but the variability of the results themselves. From a measured win rate and payoff ratio it derives the outcome standard deviation, a per-trade consistency ratio, the realistic ±1σ swing band around the expectancy, and a 0-100 consistency score.
The score feeds a position-sizing decision layer: a suggested size percentage, the score needed to reach full size, and a stand-down rule for when the edge turns negative. The signature visual renders this directly on the price scale — two outcome bars sized in real ATR-based risk units, anchored at the latest close, with the expectancy and its ±1σ swing drawn as a band between them.
It does NOT predict price direction, generate entries, or guarantee outcomes. It measures how bumpy the ride is likely to be for a given edge, and translates that into a concrete sizing decision.
🎯 Purpose & Design Philosophy
Most traders judge an edge by its average outcome alone. Two setups with the same expectancy can carry very different practical risk: one produces a narrow, predictable spread of results, while the other produces a wide spread dominated by a few large outcomes. Sizing both the same way ignores that difference.
Edge Consistency Gauge was built to make that difference visible and actionable. It supports a risk-aware, evidence-based approach to position sizing — reducing size when results are dispersed and lumpy, and allowing full size only once an edge has demonstrated real consistency.
⚡ Why This Script Is Different
Most edge- and win-rate-focused tools stop at a single expectancy number, treating a smooth edge and a lumpy edge the same as long as the average is positive.
This script does NOT treat expectancy as the whole picture, and it does NOT recommend a fixed position size regardless of how dispersed the outcomes are.
Instead, it quantifies the spread around the expectancy, scores how consistent that spread is, and ties the score directly to a sizing recommendation — full size only when the edge is demonstrably smooth, reduced size when it is choppy or lumpy, and a stand-down flag when the edge turns negative.
⚙️ Methodology
1. Measured Samples
A transparent proxy trigger — price crossing a configurable EMA — opens a simulated trade with a stop at one ATR and a target at a configurable payoff multiple (R). Whichever level is reached first resolves the trade as a win or a loss.
2. Outcome Distribution
Wins and losses form a two-point outcome distribution. From the measured win rate and payoff R, the tool derives the expectancy (mean), the outcome standard deviation (σ), and the realistic ±1σ swing band in R.
3. Consistency Score
A per-trade consistency ratio (mean ÷ σ) is mapped to a 0-100 score, with adjustable sensitivity.
4. Decision Layer
The score is mapped to a suggested position size: full size above a configurable threshold, reduced size in two lower tiers, and a stand-down (0%) rule whenever expectancy turns negative.
🗺️ How to Read the Chart
• Entry / 0R line — a short reference line and tag marking the last close, the zero point outcomes are measured from.
• Loss bar — extends down to −1R, the fixed risk unit.
• Win bar — extends up to the current payoff R.
• Shaded band — the realistic ±1σ swing around expectancy, drawn between the bars.
• Dashed line — the expectancy (average outcome) itself.
• Win / loss markers — in Measured mode, small triangles flag the resolution of each proxy trade through history.
• Decision panel — lists every metric plus the current sizing recommendation.
🚦 Signals & States
• Smooth edge → high consistency score; outcomes cluster tightly around expectancy; full size supported.
• Choppy edge → positive but dispersed; reduced size recommended.
• Lumpy edge → positive but heavily uneven; further reduced size recommended.
• Negative edge → expectancy is at or below zero; stand-down, no size recommended.
States describe the shape of the outcome distribution, not a prediction about the next trade.
🔔 Alerts Logic
This version does not include alert conditions; consistency and sizing are read from the panel and chart in real time.
🧩 Confluence Logic
Confidence in the sizing recommendation is strongest when several conditions align: a healthy sample count behind the measured win rate, a consistency score well clear of the reduced-size thresholds, and an expectancy comfortably above zero. A single strong reading on a small sample is a hypothesis, not confluence.
📊 When to Use
• Deciding how much size an already-positive edge deserves.
• Comparing how evenly or unevenly the same trigger performs across instruments and timeframes.
• Building intuition for how outcome dispersion affects the practical experience of trading an edge.
• Teaching or studying the difference between expectancy and consistency.
⚠️ When NOT to Use
• On very small samples, where the measured win rate and consistency score are not yet reliable.
• In thin, illiquid markets where the ATR-based proxy stop and target resolve erratically.
• During extreme volatility, where realized outcomes diverge sharply from the ATR risk unit.
• As a market-timing or entry tool — it evaluates outcome dispersion, not the next move.
🎛️ Key Inputs
• Win-rate source — Measured (trigger + proof engine) or Manual.
• Payoff R — the reward-to-risk that defines the win outcome.
• Trigger EMA / ATR length / Max bars in trade — shape and resolve the proxy trades.
• Proof-engine lookback — optionally limits how far back trades are simulated, for faster loading and a more recent read.
• Consistency ratio scale — calibrates how the mean/σ ratio maps to the 0-100 score.
• Position sizing thresholds — full-size and reduced-size score thresholds, and the size percentage for each tier.
• Outcome bars — show/hide, distance from the last bar, width, and vertical scale.
• Panel — show/hide, position, theme (Dark/Light), and font size.
🖥️ Interface & Visual Design
The interface separates the analytical layers cleanly: a compact decision panel for the full metric set and sizing recommendation, and a native price-scale outcome-bar pair for the at-a-glance read on the chart itself. A merged header, a fixed professional palette, and luminance-aware text keep every element legible on dark and light charts. Scores are shown numerically, never as bars.
🧪 Practical Usage Workflow
1. Read the panel — note win rate, expectancy, outcome σ, and consistency score.
2. Read the bars — see the win/loss outcomes and the ±1σ band around expectancy directly in price terms.
3. Check the verdict — Smooth, Choppy, Lumpy, or Negative.
4. Apply the suggested size — or compare it against your own sizing rules.
5. Reassess as the sample grows — consistency can improve or degrade as more trades resolve.
🔍 Interpretation Guidelines
Treat expectancy and consistency as two separate questions. A positive expectancy tells you an edge should work over time; consistency tells you how smooth or rough that path is likely to be. A high consistency score does not guarantee the next trade wins — it describes the shape of the distribution the edge has produced so far, which can and does shift as conditions change.
🚫 What This Script Is NOT
• It is NOT a prediction engine — it does not forecast price or the next trade.
• It is NOT financial advice.
• It is NOT an automated or signal-trading system.
• It does NOT guarantee any win rate, payoff, or outcome.
⚠️ Limitations & Transparency
The measured win rate depends entirely on the built-in proxy trigger, which is a stand-in for real entries and will differ from them. The outcome distribution assumes a fixed payoff R and independent trades; real trading results cluster and edges drift over time. Timeframe, volatility, and liquidity all change how the proxy trades resolve. Past consistency is not future consistency.
🧠 Market Context Notes
Outcome dispersion is a property of a process across many trades, not of any single position. Regime shifts, volatility, and liquidity all change how proxy trades resolve, which moves both the expectancy and the spread around it. Read the consistency score as a snapshot of the current sample, refreshed as conditions and trade count evolve.
🧾 Use Case Examples
• A setup shows a 69% win rate at 2.0R with a tight ±1σ swing — the consistency score reads high and the panel recommends full size.
• A setup shows a 37% win rate at 2.0R with a wide ±1σ swing dominated by occasional large wins — the consistency score reads low despite positive expectancy, and the panel recommends reduced size.
🧱 System Philosophy
AGPro tools are built to support decisions, not replace them. Edge Consistency Gauge follows that principle: it exposes the shape of an edge's outcomes transparently, ties that shape to a concrete sizing recommendation, and leaves the final decision — and the responsibility — with the trader.
🔐 Non-Promise Statement
This script makes no promises and offers no certainty. It is a statistical and visualization tool. A high consistency score describes a sample, not a guarantee of future profit.
📉 Risk Disclosure
Trading involves substantial risk of loss and is not suitable for everyone. This script is provided for educational and analytical purposes only and does not constitute financial advice or a recommendation to buy or sell any instrument. All trading decisions, and their consequences, remain entirely your own responsibility.
📚 Educational Note
Use Edge Consistency Gauge to build intuition for the difference between an edge's average outcome and its practical ride. The most valuable takeaway is not any single reading, but the habit of sizing in proportion to how consistent an edge has actually shown itself to be.
Release Notes
🔧 UPDATE NOTES - V1.0.1This focused update improves consistency-score correctness, proof-sample transparency, threshold safety, and analytical wording while preserving the original Edge Consistency Gauge concept and native R-outcome visual.
The script remains a statistical dispersion and visualization tool. It does not predict price direction, automate trading, or prescribe an actual position size.
------------------------
What Changed
------------------------
• Correct zero-dispersion scoring
A positive sample with zero outcome dispersion now receives maximum consistency instead of falling back incorrectly to the neutral midpoint. The ratio is displayed as infinity when the modeled denominator is zero.
• Proof-sample audit
The panel now reports resolved wins, resolved losses, and expired observations as W / L / X. Expired observations remain excluded from consistency scoring but are no longer invisible.
• Tier-order protection
Full/reduced score thresholds and choppy/lumpy model caps are normalized internally when users enter them in reverse order. The hierarchy therefore remains coherent without changing default behavior.
• Neutral decision language
Suggested Size is now Model Size Cap, and directive trading language was replaced with analytical baseline-cap wording.
• Transparent lookback scope
The lookback tooltip now explains that it defines the initialization history on a full recalculation; it is not a continuously rolling sample.
------------------------
Visual Improvements
------------------------
• Preserved the signature native-price R-outcome bars, centered dispersion band, mean line, compact outcome labels, and historical result markers
• Added a compact Proof Audit row while retaining the established panel hierarchy
• Rebuilt the blue panel title after every clear, merged it across the full width, and then wrote only the script name
• Preserved the AGPro palette and contrast-aware label text
------------------------
Interface & Usability
------------------------
• Outcome boxes, lines, and labels now clear deterministically when Show outcome bars is disabled
• Position-model input labels now describe thresholds and caps rather than direct trading instructions
• The visible Model ±1σ row distinguishes a mathematical distribution band from a guaranteed or “realistic” future range
------------------------
Behavior Notes
------------------------
The two-point outcome distribution, EMA-cross trigger, ATR risk unit, payoff-R model, expectancy, standard deviation, historical outcome markers, and chart-native outcome-bar geometry remain unchanged.
Defaults produce the same tier structure. Results can differ only for zero-dispersion samples, reversed custom tier inputs, or the newly visible timeout audit.
------------------------
Limitations Reminder
------------------------
The measured sample belongs to the built-in EMA-cross proxy, not necessarily to a user’s strategy. Expired observations are excluded, which can create selection bias. OHLC bars cannot reveal intrabar order when stop and target are both touched; the engine retains its conservative stop-first convention.
The model assumes fixed +R / −1R outcomes. Real fills, partial exits, gaps, costs, clustered results, and changing market regimes can produce a different distribution.
------------------------
Risk Reminder
------------------------
This script is for educational and analytical purposes only.
Model caps are comparative outputs, not financial advice or position-sizing instructions. Users remain responsible for their own risk limits and decisions.
Release Notes
🔧 UPDATE NOTES - V1.0.2• Refreshed the publication and access routing information.
• Core edge-consistency logic, panel behavior, inputs, alerts, visuals, and outputs remain unchanged.
Release Notes
🔧 UPDATE NOTES - V1.0.3This update focuses on evidence quality, visual identity, compact presentation, and safer interpretation.
The two-outcome consistency model remains unchanged. This release improves how measured evidence is resolved, graded, and presented.
------------------------
What Changed
------------------------
• Added explicit same-bar target/stop handling with Exclude, Stop First, and Target First modes.
• Added a configurable full-tier minimum sample threshold.
• A high consistency score below the required measured sample count now receives the PROVISIONAL SMOOTH verdict instead of opening the full baseline tier.
• Added a show/hide control for historical win and loss markers.
• Separated chart-label font size from panel font size.
------------------------
Visual Improvements
------------------------
• Added a prominent CONSISTENCY score-and-verdict badge above the native outcome bars.
• Increased the default outcome-bar width for a stronger first-glance profile.
• Added a visible border to the modeled 1σ dispersion band.
• Preserved the distinctive win/loss bar pair, entry reference, mean line, and average-outcome readout.
------------------------
Interface & Usability
------------------------
• Reduced the decision panel from 15 rows to 10 rows.
• Combined related metrics into Win / Payoff and Mean / Sigma rows.
• Replaced long instructional text with a compact Read field.
• Added a concise evidence readout showing progress toward the full-tier sample requirement.
• Preserved panel visibility, position, theme, and font-size controls.
------------------------
Behavior Notes
------------------------
The core expectancy, outcome sigma, consistency ratio, and consistency score calculations are unchanged.
Measured mode now requires both the configured consistency score and the configured minimum sample count before the 100% baseline model tier can open.
The model percentage remains an analytical cap relative to a user-defined baseline. It is not a position-size instruction.
------------------------
Limitations Reminder
------------------------
The script remains a rule-based analytical tool built from a transparent proxy trigger and fixed outcome assumptions.
Sample size, timeframe, volatility, liquidity, and same-bar ambiguity can affect measured results.
------------------------
Risk Reminder
------------------------
This script is for educational and analytical purposes only.
It does not provide financial advice or guaranteed trading outcomes.
Users remain responsible for their own decisions.
Release Notes
UPDATE NOTES - V1.0.4This update focuses on presentation clarity and evidence readability.
The core purpose of the script remains unchanged.
This release improves how the existing consistency model is organized and interpreted on the chart.
This script continues to function as an analytical and visualization tool.
It does not attempt to predict price direction or provide guaranteed outcomes.
------------------------
What Changed
------------------------
- Added a full-width analytical question below the panel title:
"IS THIS EDGE CONSISTENT ACROSS TRADES?"
- Replaced the compact A / X audit shorthand with explicit ambiguous and expired outcome counts.
- Expanded the panel by one row so every metric keeps a dedicated, readable position.
- Preserved the existing expectancy, dispersion, evidence, and sizing-cap framework.
------------------------
Visual Improvements
------------------------
- Improved the panel's first-glance information hierarchy.
- Kept the chart-native outcome profile compact and free of label overlap.
- Preserved the existing AGPro color system and light-chart readability.
------------------------
Interface & Usability
------------------------
- Retained the configurable panel position, theme, visibility, and font sizing.
- Made the proof audit understandable without relying on internal abbreviations.
- Kept the panel width unchanged while adding the new interpretation anchor.
------------------------
Behavior Notes
------------------------
This update does not change the core analytical logic of the script.
Expectancy, outcome sigma, the +/-1 sigma band, consistency ratio, consistency score, evidence gate, model cap, signals, alerts, and outcome bars remain unchanged.
------------------------
Limitations Reminder
------------------------
The script remains a rule-based analytical tool.
Its output depends on the selected win-rate source, payoff assumption, sample depth, symbol, timeframe, and market conditions.
------------------------
Risk Reminder
------------------------
This script is for educational and analytical purposes only.
It does not provide financial advice or guaranteed trading outcomes.
Users remain responsible for their own decisions.
Release Notes
🔧 UPDATE NOTES - V1.1.0This update focuses on chart readability, visual ownership, performance discipline, and panel hierarchy.
The core purpose of the script remains unchanged. This release improves how the existing consistency model is presented and interpreted on the chart.
• Refined the signature R-outcome composition while preserving the original dispersion and consistency calculations.
• Moved the entry reference into a dedicated left-side lane and added an owned connector to prevent overlap with the outcome bars.
• Added a separate connector for the average-outcome readout and increased its font-aware horizontal clearance.
• Increased font-aware spacing above the win bar so the consistency verdict remains readable across all label sizes.
• Limited historical win/loss markers to an adjustable recent-bar window, with a balanced 1,200-bar default.
• Reduced visual object budgets to match the script's actual persistent footprint and support faster chart rendering.
• Added alternating dark/light panel rows while preserving the merged blue title and analytical question.
• Preserved the measured proof engine, same-bar ambiguity handling, expiry audit, outcome dispersion model, decision tiers, and all analytical behavior.
This script remains a rule-based analytical and visualization tool. It does not predict price direction, automate trades, provide financial advice, or guarantee outcomes. Market conditions, timeframe selection, sample depth, and input assumptions may affect interpretation. Users remain responsible for their own decisions.
Invite-only script
Only users approved by the author can access this script. You'll need to request and get permission to use it. This is typically granted after payment. For more details, follow the author's instructions below or contact AGProLabs directly.
TradingView does NOT recommend paying for or using a script unless you fully trust its author and understand how it works. You may also find free, open-source alternatives in our community scripts.
Author's instructions
Request access to Edge Consistency Gauge [AGPro Series]:
https://www.agprolabs.com/product/edge-consistency-gauge/
🧠 Trading Suite - Flagship Workflow
tradingview.com/script/XJmX3p98-Trading-Suite-AGPro-Series/
🔷 Crypto Setup Planner - Multi-Symbol Planner
tradingview.com/script/LgVRo7Ql-Crypto-Setup-Planner-AGPro-Series/
tradingview.com/script/XJmX3p98-Trading-Suite-AGPro-Series/
🔷 Crypto Setup Planner - Multi-Symbol Planner
tradingview.com/script/LgVRo7Ql-Crypto-Setup-Planner-AGPro-Series/
Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.
Invite-only script
Only users approved by the author can access this script. You'll need to request and get permission to use it. This is typically granted after payment. For more details, follow the author's instructions below or contact AGProLabs directly.
TradingView does NOT recommend paying for or using a script unless you fully trust its author and understand how it works. You may also find free, open-source alternatives in our community scripts.
Author's instructions
Request access to Edge Consistency Gauge [AGPro Series]:
https://www.agprolabs.com/product/edge-consistency-gauge/
🧠 Trading Suite - Flagship Workflow
tradingview.com/script/XJmX3p98-Trading-Suite-AGPro-Series/
🔷 Crypto Setup Planner - Multi-Symbol Planner
tradingview.com/script/LgVRo7Ql-Crypto-Setup-Planner-AGPro-Series/
tradingview.com/script/XJmX3p98-Trading-Suite-AGPro-Series/
🔷 Crypto Setup Planner - Multi-Symbol Planner
tradingview.com/script/LgVRo7Ql-Crypto-Setup-Planner-AGPro-Series/
Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.