diff --git a/scripts/analyze.py b/scripts/analyze.py
index cb6621d..4612287 100644
--- a/scripts/analyze.py
+++ b/scripts/analyze.py
@@ -805,6 +805,18 @@ Ko najdeš lyrics:
 - Identificiraj BRIDGE / PRE-CHORUS / OUTRO če obstajajo
 - Mapiraj transkript timestamp-e na strukturne dele
 - Popravi corrected_segments z dejanskim besedilom
+
+🎯 **POMEMBNA HEVRISTIKA: NASLOV PESMI = REFREN HOOK**:
+Naslov pesmi je v 80-90% primerov **ključna fraza refrena** (hook). 
+- "Pijan" → refren vsebuje "pijan, pijan"
+- "Brajde" → refren vsebuje "brajde" (ne pa pre-chorus o traktorju!)
+- "Žena me tepe" → refren = "Žena me tepe"
+- "Stisn se k men" → refren = "Stisni se k meni"
+- "Cvetele so maline" → refren vsebuje "cvetele so maline" ali povezano
+
+Če iz transkripta ne najdeš naslovne fraze blizu izbranega clipa, **VERJETNO si izbral verz/pre-chorus, ne refrena**. Poišči pravi refren.
+
+⚠️ **PAZI**: prvi verz pesmi se pogosto začne **takoj po intro-u** (5-15s) in je kontekstualen — TO NI REFREN. Refren običajno pride **po prvem verzu** (pri 30-60s, odvisno od pesmi).
 """
 
     return f"""Tu je transcript pesmi iz STT modela (timestamp v sekundah, besedilo):
@@ -1327,20 +1339,53 @@ def main():
         # llm_source npr. "claude:claude-sonnet-4-6" ali "gemini:gemini-3.1-pro-preview".
         if claude_result:
             llm_source = claude_result.get("source", "llm")
-            clip_range = {
-                "start": claude_result["start"],
-                "end": claude_result["end"],
-                "duration": claude_result["duration"],
-                "reason": f"{llm_source}: " + claude_result.get("reason", ""),
-                "chorus_text": claude_result.get("chorus_text", ""),
-                "structure": claude_result.get("structure", ""),
-                "source": llm_source,
-            }
-            # Apply max_duration cap če LLM pretirava
-            if clip_range["duration"] > args.max_duration:
-                clip_range["end"] = clip_range["start"] + args.max_duration
-                clip_range["duration"] = args.max_duration
-                clip_range["reason"] += " (capped at max_duration)"
+            
+            # ── HALUCINACIJA HANDLING ──
+            # Če je Claude detect-iral halucinacijo (npr. Scribe je vrnil
+            # "finančni moduli" namesto pesmi), NE zaupamo izbiri clipa,
+            # ker LLM ni mogel locirati pravega refrena.
+            if claude_result.get("hallucination_detected"):
+                print(f"⚠️ HALUCINACIJA DETECT-ANA — fallback na local heuristic "
+                      f"(Scribe transkript ne ustreza zvočnemu vsebini)", file=sys.stderr)
+                # Reset claude_result — gremo na local fallback
+                clip_range = smart_clip_range(
+                    chorus, transcript, duration,
+                    target_duration=args.target_duration,
+                    max_duration=args.max_duration,
+                    min_duration=args.min_duration,
+                    include_prebuild=args.include_prebuild,
+                )
+                clip_range["source"] = "local_fallback_after_hallucination"
+                clip_range["reason"] = (
+                    "STT halucinacija — local heuristic fallback. "
+                    "Refren je iz energy-based detekcije, ne iz transkripta. "
+                    + clip_range.get("reason", "")
+                )
+                claude_result = None  # disable extensions
+            else:
+                clip_range = {
+                    "start": claude_result["start"],
+                    "end": claude_result["end"],
+                    "duration": claude_result["duration"],
+                    "reason": f"{llm_source}: " + claude_result.get("reason", ""),
+                    "chorus_text": claude_result.get("chorus_text", ""),
+                    "structure": claude_result.get("structure", ""),
+                    "source": llm_source,
+                }
+                # Apply max_duration cap če LLM pretirava
+                if clip_range["duration"] > args.max_duration:
+                    clip_range["end"] = clip_range["start"] + args.max_duration
+                    clip_range["duration"] = args.max_duration
+                    clip_range["reason"] += " (capped at max_duration)"
+                
+                # Apply min_duration floor — če je clip prekratek, podaljšaj
+                if clip_range["duration"] < args.min_duration:
+                    needed = args.min_duration - clip_range["duration"]
+                    new_end = min(clip_range["end"] + needed, duration)
+                    actual_extension = new_end - clip_range["end"]
+                    clip_range["end"] = new_end
+                    clip_range["duration"] = clip_range["end"] - clip_range["start"]
+                    clip_range["reason"] += f" (extended +{actual_extension:.1f}s to meet min_duration)"
 
             # ── EXTEND clip end do naslednje naravne pavze ──
             # LLM pogosto reže točno na zadnji besedi refrena, ampak zadnja
@@ -1375,8 +1420,11 @@ def main():
             current_start = clip_range["start"]
             
             # Zberi VSE besede z njihovimi timestampi
+            # POMEMBNO: Claude corrected_segments NE vsebuje word-level timestamps,
+            # samo segment start/end. Word-level je samo v originalnem Scribe transkriptu.
+            # Zato vedno uporabi `transcript["segments"]` ne `corrected_segs`.
             all_words = []
-            for seg in corrected_segs:
+            for seg in transcript.get("segments", []):
                 for w in seg.get("words", []):
                     if w.get("start") is not None and w.get("end") is not None:
                         all_words.append({