diff --git a/.github/copilot-instructions.md b/.github/copilot-instructions.md
index a876d35..c916106 100644
--- a/.github/copilot-instructions.md
+++ b/.github/copilot-instructions.md
@@ -720,14 +720,20 @@ WHERE "blockReason" = 'QUALITY_SCORE_TOO_LOW'
 - **Comprehensive:** Tracks best/worst case scenarios (MFE/MAE)
 - **API accessible:** Check status anytime via `/api/analytics/signal-tracking`
 
-**Current Status (Nov 22, 2025):**
+**Current Status (Nov 26, 2025):**
 - ✅ System deployed and running in production
 - ✅ **Enhanced Nov 22:** Now tracks quality-blocked signals (QUALITY_SCORE_TOO_LOW) in addition to multi-timeframe data collection
+- ✅ **Enhanced Nov 26:** Quality scoring now calculated for ALL timeframes (not just 5min production signals)
+  - Execute endpoint calculates `scoreSignalQuality()` BEFORE timeframe check (line 112)
+  - Data collection signals now get real quality scores (not hardcoded 0)
+  - BlockedSignal records include: `signalQualityScore` (0-100), `signalQualityVersion` ('v9'), `minScoreRequired` (90/95)
+  - Enables SQL queries: `WHERE signalQualityScore >= minScoreRequired` to compare quality-filtered win rates
+  - Commit: dbada47 "feat: Calculate quality scores for all timeframes (not just 5min)"
 - ✅ TradingView alerts configured for 15min and 1H
 - ✅ Background tracker runs every 5 minutes autonomously
 - 📊 **Data collection:** Multi-timeframe (50+ per timeframe) + quality-blocked (20-30 signals)
 - 🎯 **Dual goals:** 
-  1. Determine which timeframe has best win rate
+  1. Determine which timeframe has best win rate (now with quality filtering capability)
   2. Validate if quality 91 threshold filters winners or losers
 - 📈 **First result (Nov 21, 16:50):** Quality 80 signal blocked (weak ADX 16.6), would have profited +0.52% (+$43) within 1 minute - **FALSE NEGATIVE confirmed**
 
@@ -1315,7 +1321,9 @@ TradingView alert → n8n Parse Signal Enhanced (extracts metrics + timeframe)
   ↓ /api/trading/execute
   ↓ normalize symbol (SOLUSDT → SOL-PERP)
   ↓ getMergedConfig()
-  ↓ scoreSignalQuality({ ..., timeframe }) [CRITICAL: calculate EARLY, before position sizing]
+  ↓ scoreSignalQuality({ ..., timeframe }) [CRITICAL: calculate EARLY for ALL timeframes - line 112, Nov 26]
+  ↓ IF timeframe !== '5': Save to BlockedSignal with quality scores → return success
+  ↓ IF timeframe === '5': Continue to execution (production trade)
   ↓ getPositionSizeForSymbol(qualityScore) [adaptive leverage based on quality score]
   ↓ openPosition() [MARKET order with adaptive leverage]
   ↓ calculate dual stop prices if enabled
@@ -1324,6 +1332,15 @@ TradingView alert → n8n Parse Signal Enhanced (extracts metrics + timeframe)
   ↓ positionManager.addTrade() [ONLY after DB save succeeds - prevents unprotected positions]
 ```
 
+**CRITICAL EXECUTION ORDER (Nov 26, 2025 - Multi-Timeframe Quality Scoring):**
+Quality scoring MUST happen BEFORE timeframe filtering - this is NOT arbitrary:
+- All timeframes (5min, 15min, 1H, 4H, Daily) need real quality scores for analysis
+- Data collection signals (15min+) save to BlockedSignal with full quality metadata
+- Enables SQL queries: `WHERE blockReason = 'DATA_COLLECTION_ONLY' AND signalQualityScore >= X`
+- Purpose: Compare quality-filtered win rates across timeframes to determine optimal trading interval
+- Old flow: Timeframe check → Quality score only for 5min → Data collection signals get hardcoded 0
+- **New flow:** Quality score ALL signals → Timeframe routing → Data collection gets real scores
+
 **CRITICAL EXECUTION ORDER (Nov 24, 2025 - Adaptive Leverage):**
 The order of quality scoring → position sizing is NOT arbitrary - it's a requirement:
 - Quality score MUST be calculated BEFORE position sizing
@@ -4274,6 +4291,14 @@ if (!enabled) {
     - Create reference docs in `docs/` for complex features (e.g., `MANUAL_TRADE_FILTERING.md`)
     - **WHY:** Future AI agents need complete context to maintain data integrity and avoid breaking analysis
     - **EXAMPLES:** signalSource field for filtering, MAE/MFE tracking, phantom trade detection
+19. **MULTI-TIMEFRAME DATA COLLECTION CHANGES (Nov 26, 2025):** When modifying signal processing for different timeframes:
+    - Quality scoring MUST happen BEFORE timeframe filtering (execute endpoint line 112)
+    - All timeframes need real quality scores for analysis (not hardcoded 0)
+    - Data collection signals (15min/1H/4H/Daily) save to BlockedSignal with full quality metadata
+    - BlockedSignal fields to populate: signalQualityScore, signalQualityVersion, minScoreRequired, scoreBreakdown
+    - Enables SQL: `WHERE blockReason = 'DATA_COLLECTION_ONLY' AND signalQualityScore >= X`
+    - Purpose: Compare quality-filtered win rates across timeframes to determine optimal trading interval
+    - Update Multi-Timeframe section in copilot-instructions.md when changing flow
 
 ## Development Roadmap