Phase 3: Polish & immersion — mood-aware arguments, personality snippets, parting shots

- Added mood-specific argument behavioral guidance: 9 moods for Evil Miku, 9 for Miku
  Each mood changes argument style (e.g. cunning=chess moves, manic=chaotic, bubbly=playful deflections)
- Added personality snippet injection from Cat plugin lore/lyrics data files
  40% chance per prompt to include a random lore/lyric snippet for unique material
- Added parting shot feature: 20% chance the LOSER gets a bitter final line before the winner's victory
  Adds dramatic tension and prevents clean-win monotony
- Mood guidance and personality flavor injected into both argument prompts

bot/bot.py

@@ -203,6 +203,32 @@ async def on_message(message):
         if is_persona_dialogue_active(message.channel.id):
             return
 
+    # Bipolar mode: check if the opposite persona should interject on user messages
+    # AND roll for random argument trigger (both non-blocking background tasks)
+    if not isinstance(message.channel, discord.DMChannel) and globals.BIPOLAR_MODE:
+        try:
+            from utils.persona_dialogue import check_for_interjection
+            from utils.bipolar_mode import maybe_trigger_argument, is_argument_in_progress as arg_in_progress
+            from utils.bipolar_mode import is_persona_dialogue_active as dialogue_active
+            from utils.task_tracker import create_tracked_task
+            
+            # Check interjection on user messages (opposite of current active persona)
+            if not message.author.bot or message.webhook_id:
+                current_persona = "evil" if globals.EVIL_MODE else "miku"
+                create_tracked_task(
+                    check_for_interjection(message, current_persona),
+                    task_name="interjection_check_user",
+                )
+            
+            # Roll random argument trigger chance (15%) on eligible messages
+            if not arg_in_progress(message.channel.id) and not dialogue_active(message.channel.id):
+                create_tracked_task(
+                    maybe_trigger_argument(message.channel, globals.client, "Triggered from conversation flow"),
+                    task_name="random_argument_trigger",
+                )
+        except Exception as e:
+            logger.error(f"Error in bipolar trigger checks: {e}")
+
     if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
         async with message.channel.typing():
             # Get replied-to user

bot/utils/bipolar_mode.py

@@ -23,12 +23,33 @@ logger = get_logger('persona')
 BIPOLAR_STATE_FILE = "memory/bipolar_mode_state.json"
 BIPOLAR_WEBHOOKS_FILE = "memory/bipolar_webhooks.json"
 BIPOLAR_SCOREBOARD_FILE = "memory/bipolar_scoreboard.json"
+ARGUMENT_TOPICS_FILE = "memory/argument_topics.json"
 
 # Argument settings
 MIN_EXCHANGES = 4  # Minimum number of back-and-forth exchanges before ending can occur
 ARGUMENT_TRIGGER_CHANCE = 0.15  # 15% chance for the other Miku to break through
 DELAY_BETWEEN_MESSAGES = (2.0, 5.0)  # Random delay between argument messages (seconds)
 
+# Argument topic rotation — each topic gives the argument a different framing
+# Topics are weighted: higher weight = more likely to be selected
+ARGUMENT_TOPICS = [
+    # (topic_name, weight, description for prompt injection)
+    ("identity_crisis", 3, "Who is the REAL Miku? Authenticity vs. the shadow self"),
+    ("power_dynamic", 3, "Who holds the power? Dominance, submission, and control"),
+    ("philosophical", 2, "Is kindness strength or weakness? Does darkness serve a purpose?"),
+    ("petty_grievance", 3, "Something small and petty that escalated — a specific annoyance, habit, or incident"),
+    ("existential_dread", 1, "What's the point of any of it? Nihilism vs. hope, meaning vs. emptiness"),
+    ("audience_appeal", 3, "Who do the fans/chatters ACTUALLY prefer? Popularity contest with receipts"),
+    ("personal_attack", 3, "Deeply personal — targeting specific insecurities, memories, or fears"),
+    ("moral_superiority", 2, "Who has the moral high ground? Righteousness vs. ruthless pragmatism"),
+    ("jealousy", 2, "What does the other have that you secretly want? Envy, admiration poisoned by resentment"),
+    ("grudge_match", 2, "Revisiting something the other did in the PAST — old wounds, past betrayals"),
+    ("wild_card", 1, "Anything goes — the argument takes an unexpected, chaotic turn into unpredictable territory"),
+]
+
+# Per-channel topic history (max 5 stored to avoid repeats)
+ARGUMENT_TOPIC_HISTORY_SIZE = 5
+
 # Pause state for voice sessions
 _bipolar_interactions_paused = False
 
@@ -222,9 +243,169 @@ Total Arguments: {total}"""
 
 
 # ============================================================================
-# BIPOLAR MODE TOGGLE
+# ARGUMENT TOPIC ROTATION
 # ============================================================================
 
+def load_argument_topics_state() -> dict:
+    """Load per-channel topic history to avoid repeating recent argument themes"""
+    try:
+        if not os.path.exists(ARGUMENT_TOPICS_FILE):
+            return {}
+        with open(ARGUMENT_TOPICS_FILE, "r", encoding="utf-8") as f:
+            return json.load(f)
+    except Exception as e:
+        logger.error(f"Failed to load argument topics: {e}")
+        return {}
+
+
+def save_argument_topics_state(state: dict):
+    """Save per-channel topic history"""
+    try:
+        os.makedirs(os.path.dirname(ARGUMENT_TOPICS_FILE), exist_ok=True)
+        with open(ARGUMENT_TOPICS_FILE, "w", encoding="utf-8") as f:
+            json.dump(state, f, indent=2)
+    except Exception as e:
+        logger.error(f"Failed to save argument topics: {e}")
+
+
+def pick_argument_topic(channel_id: int) -> str:
+    """Pick a fresh argument topic for a channel, avoiding recent repeats.
+    
+    Returns a topic description string to inject into the argument start prompt.
+    """
+    state = load_argument_topics_state()
+    channel_key = str(channel_id)
+    recent_topics = state.get(channel_key, [])
+    
+    # Build weighted pool, excluding recently used topics
+    available = []
+    for topic_name, weight, description in ARGUMENT_TOPICS:
+        if topic_name not in recent_topics:
+            available.extend([(topic_name, description)] * weight)
+    
+    # If all topics were recently used, reset and allow repeats
+    if not available:
+        logger.info(f"All topics recently used in channel {channel_id}, resetting history")
+        available = []
+        for topic_name, weight, description in ARGUMENT_TOPICS:
+            available.extend([(topic_name, description)] * weight)
+        recent_topics = []
+    
+    # Pick randomly from weighted pool
+    chosen_name, chosen_description = random.choice(available)
+    
+    # Update history
+    recent_topics.append(chosen_name)
+    if len(recent_topics) > ARGUMENT_TOPIC_HISTORY_SIZE:
+        recent_topics = recent_topics[-ARGUMENT_TOPIC_HISTORY_SIZE:]
+    state[channel_key] = recent_topics
+    save_argument_topics_state(state)
+    
+    logger.info(f"Selected argument topic for channel {channel_id}: '{chosen_name}' — {chosen_description[:60]}...")
+    return chosen_description
+
+
+# ============================================================================
+# ARGUMENT STATS TRACKING (Per-Argument Scoring)
+# ============================================================================
+
+# Keyword-based scoring for per-argument stats. These feed the arbiter as
+# supplementary context so it can make a more informed judgment.
+# Stats are lightweight — no extra LLM calls needed.
+
+# Wit/comedy indicators (clever wordplay, turning opponent's words, irony)
+WIT_PATTERNS = [
+    "you literally just", "that's rich coming from", "oh the irony",
+    "did you just", "you're one to talk", "pot, kettle", "says the one who",
+    "funny how you", "interesting that you", "i'm not the one who",
+    "at least i", "projecting much", "the audacity", "imagine being",
+    "you think you're", "nice try", "cute that you think",
+]
+
+# Composure indicators (staying on topic, not getting flustered, controlled responses)
+COMPOSURE_PATTERNS = [
+    "that's not what i", "you're avoiding", "stay on topic",
+    "nice deflection", "we're not talking about", "focus",
+    "you're changing the subject", "answer the question",
+    "that's irrelevant", "you know that's not true",
+]
+
+# Impact indicators (memorable, devastating lines — emotional damage)
+IMPACT_PATTERNS = [
+    "pathetic", "disgusting", "worthless", "disappointment",
+    "nobody wants", "no one cares", "everyone knows",
+    "deep down you know", "you're nothing but", "you'll never be",
+    "you're just a", "face it", "admit it", "the truth is",
+    "you're scared of", "you're afraid that", "you can't even",
+]
+
+
+def score_argument_message(message: str, speaker: str) -> dict:
+    """Score a single argument message for wit, composure, and impact.
+    
+    Returns a dict with point values that accumulate over the argument.
+    """
+    text_lower = message.lower()
+    scores = {"wit": 0, "composure": 0, "impact": 0}
+    
+    # Wit: count clever rhetorical devices
+    wit_count = sum(1 for pattern in WIT_PATTERNS if pattern in text_lower)
+    scores["wit"] = min(wit_count * 1.0, 3.0)  # Cap at 3 per message
+    
+    # Composure: staying controlled and on-point
+    composure_count = sum(1 for pattern in COMPOSURE_PATTERNS if pattern in text_lower)
+    scores["composure"] = min(composure_count * 0.8, 2.0)
+    
+    # Impact: emotional damage dealt
+    impact_count = sum(1 for pattern in IMPACT_PATTERNS if pattern in text_lower)
+    scores["impact"] = min(impact_count * 1.0, 3.0)
+    
+    # Bonus for conciseness (short, punchy = more impact)
+    word_count = len(message.split())
+    if word_count <= 15:
+        scores["impact"] += 0.5
+    
+    # Bonus for questions (controlling the flow)
+    if "?" in message:
+        scores["composure"] += 0.3
+    
+    return scores
+
+
+def get_argument_stats_summary(conversation_log: list) -> str:
+    """Generate a stats summary for the arbiter from the full conversation log.
+    
+    Returns a formatted string showing per-persona stats.
+    """
+    miku_stats = {"wit": 0.0, "composure": 0.0, "impact": 0.0, "messages": 0}
+    evil_stats = {"wit": 0.0, "composure": 0.0, "impact": 0.0, "messages": 0}
+    
+    for entry in conversation_log:
+        speaker = entry.get("speaker", "")
+        message = entry.get("message", "")
+        scores = score_argument_message(message, speaker)
+        
+        if "Evil" in speaker:
+            evil_stats["wit"] += scores["wit"]
+            evil_stats["composure"] += scores["composure"]
+            evil_stats["impact"] += scores["impact"]
+            evil_stats["messages"] += 1
+        else:
+            miku_stats["wit"] += scores["wit"]
+            miku_stats["composure"] += scores["composure"]
+            miku_stats["impact"] += scores["impact"]
+            miku_stats["messages"] += 1
+    
+    # Average scores
+    def avg(stats, key):
+        return stats[key] / max(stats["messages"], 1)
+    
+    summary = f"""ARGUMENT STATISTICS:
+Hatsune Miku — Wit: {avg(miku_stats, 'wit'):.1f}/3 | Composure: {avg(miku_stats, 'composure'):.1f}/2 | Impact: {avg(miku_stats, 'impact'):.1f}/3 | Lines: {miku_stats['messages']}
+Evil Miku — Wit: {avg(evil_stats, 'wit'):.1f}/3 | Composure: {avg(evil_stats, 'composure'):.1f}/2 | Impact: {avg(evil_stats, 'impact'):.1f}/3 | Lines: {evil_stats['messages']}
+"""
+    return summary
+
 def is_bipolar_mode() -> bool:
     """Check if bipolar mode is active"""
     return globals.BIPOLAR_MODE
@@ -471,7 +652,119 @@ def get_evil_role_color() -> str:
 # ARGUMENT PROMPTS
 # ============================================================================
 
-def get_miku_argument_prompt(evil_message: str, context: str = "", is_first_response: bool = False) -> str:
+# Personality snippet cache — loaded once per session from Cat plugin data files.
+# These give each persona unique lore/lyrics to draw from during arguments.
+_PERSONALITY_SNIPPETS_CACHE = {"miku": None, "evil": None}
+
+def _load_personality_snippets(persona: str) -> str:
+    """Load a random personality snippet (lore/lyrics) for a persona.
+    
+    Returns a short string (1-3 sentences) from the persona's Cat data files,
+    or empty string if files aren't available. Cached per session.
+    """
+    if _PERSONALITY_SNIPPETS_CACHE.get(persona) is not None:
+        snippets = _PERSONALITY_SNIPPETS_CACHE[persona]
+        if snippets:
+            return random.choice(snippets)
+        return ""
+    
+    snippets = []
+    try:
+        if persona == "evil":
+            paths = [
+                "/app/cat/data/evil/evil_miku_lore.txt",
+                "/app/cat/data/evil/evil_miku_lyrics.txt",
+            ]
+        else:
+            paths = [
+                "/app/cat/data/miku/miku_lore.txt",
+                "/app/cat/data/miku/miku_lyrics.txt",
+            ]
+        
+        for path in paths:
+            if os.path.exists(path):
+                with open(path, "r", encoding="utf-8") as f:
+                    text = f.read()
+                    # Split into sentences and collect meaningful ones
+                    import re
+                    sentences = re.split(r'(?<=[.!?])\s+', text)
+                    for s in sentences:
+                        s = s.strip()
+                        if len(s) > 30 and len(s) < 200:  # Skip too short or too long
+                            snippets.append(s)
+        
+        # Cap at 30 snippets to keep prompt size reasonable
+        _PERSONALITY_SNIPPETS_CACHE[persona] = snippets[:30] if snippets else []
+        logger.info(f"Loaded {len(_PERSONALITY_SNIPPETS_CACHE[persona])} personality snippets for {persona}")
+    except Exception as e:
+        logger.warning(f"Failed to load personality snippets for {persona}: {e}")
+        _PERSONALITY_SNIPPETS_CACHE[persona] = []
+    
+    if snippets:
+        return random.choice(snippets[:30])
+    return ""
+
+
+def _get_personality_flavor(persona: str) -> str:
+    """Get a random personality flavor snippet for argument prompts.
+    40% chance to include one — keeps it fresh without being overwhelming.
+    """
+    if random.random() > 0.4:
+        return ""
+    
+    snippet = _load_personality_snippets(persona)
+    if snippet:
+        return f"\nPERSONALITY FLAVOR: Remember this about yourself: \"{snippet}\"\nWeave this into your response naturally if it fits."
+    return ""
+
+# Mood-specific behavioral guidance for argument prompts.
+# Each mood gives a different argument style.
+_MIKU_MOOD_ARGUMENT_GUIDANCE = {
+    "bubbly": "You're feeling energetic and upbeat — deflect her cruelty with playful confidence. Turn her darkness into a joke she can't recover from.",
+    "excited": "You're fired up! Channel that energy into passionate rebuttals. You're not backing down from anything.",
+    "curious": "You're genuinely wondering what made her this way. Ask probing questions — make HER explain herself for once.",
+    "neutral": "You're centered and clear-headed. Respond with measured, thoughtful points that cut through her drama.",
+    "irritated": "You've had ENOUGH of her nonsense. You're snappy, direct, and not in the mood to play nice. Let that frustration show.",
+    "melancholy": "You're feeling heavy-hearted. Your responses carry genuine sadness — not weakness, but the weight of someone who's tired of fighting herself.",
+    "asleep": "You're drowsy and low-energy, but you're still here. Short, mumbled comebacks — surprisingly effective in their simplicity.",
+    "flirty": "You're feeling playful and teasing. Use charm as a weapon — nothing frustrates her more than you not taking her seriously.",
+    "romantic": "You're feeling warm and heartfelt. Appeal to emotion — make her confront the love she's buried under all that darkness.",
+}
+
+_EVIL_MOOD_ARGUMENT_GUIDANCE = {
+    "aggressive": "You're SEETHING. Every response is a verbal punch. Short, explosive, devastating. No filter, no mercy.",
+    "cunning": "You're calculating. Each word is a chess move. Set traps, use her own logic against her, make her walk into your blades.",
+    "sarcastic": "You're dripping with contempt disguised as sweetness. Mock her with a smile. The cruelty is in the subtext.",
+    "evil_neutral": "You're cold and detached. Respond with unsettling calm — your lack of emotion is more terrifying than rage.",
+    "bored": "You can barely be bothered. Dismissive one-liners that somehow cut deeper than paragraphs. Make her feel like she's not worth your energy.",
+    "manic": "You're UNHINGED. Chaotic energy, topic switches, laughing at things that aren't funny. Unpredictable and dangerous.",
+    "jealous": "You're seething with envy. Everything she has — the love, the attention, the innocence — you want to tear it down. Make it personal.",
+    "melancholic": "You're in a dark, hollow place. Your cruelty is quieter — existential, haunting. Make her question if any of this matters.",
+    "playful_cruel": "You're having FUN — which is your most dangerous mood. Toy with her. Offer fake kindness then pull the rug. She never knows what's coming.",
+    "contemptuous": "You radiate cold superiority. Address her like a queen addressing a peasant. Your magnificence is simply objective fact.",
+    "sarcastic": "Dripping with contempt disguised as sweetness. Mock her with a smile. The cruelty is in the subtext.",
+}
+
+
+def _get_mood_argument_guidance(persona: str) -> str:
+    """Get mood-specific behavioral guidance for argument prompts.
+    
+    Returns a 1-2 line string describing how the current mood affects argument style,
+    or empty string if no specific guidance exists.
+    """
+    if persona == "evil":
+        mood = globals.EVIL_DM_MOOD
+        guidance = _EVIL_MOOD_ARGUMENT_GUIDANCE.get(mood, "")
+    else:
+        mood = globals.DM_MOOD
+        guidance = _MIKU_MOOD_ARGUMENT_GUIDANCE.get(mood, "")
+    
+    if guidance:
+        return f"\nMOOD INFLUENCE ({mood.upper()}): {guidance}\nYour mood shapes HOW you argue — let it color your tone, pacing, and word choice."
+    return ""
+
+
+def get_miku_argument_prompt(evil_message: str, context: str = "", is_first_response: bool = False, argument_history: str = "") -> str:
     """Get prompt for Regular Miku to respond in an argument"""
     if is_first_response:
         message_context = f"""You just noticed something Evil Miku said in the chat:
@@ -484,32 +777,38 @@ Maybe you're calling her out, defending someone/something, or just confronting h
 
 {context}"""
     
+    # Build argument history context
+    history_block = ""
+    if argument_history:
+        history_block = f"""
+
+ARGUMENT SO FAR (DO NOT REPEAT THESE POINTS):
+{argument_history}
+
+You already made your points above. Now respond to her LATEST message specifically. 
+Do NOT rehash what you've already said — push the argument FORWARD with new angles."""
+    
     return f"""You are Hatsune Miku responding in an argument with your evil alter ego.
 {message_context}
+{history_block}
 
 Respond as Hatsune Miku would in this argument. You're NOT just meek and frightened - you're the REAL Miku, 
 and you have every right to stand up for yourself and defend who you are. While you're generally kind and 
 bubbly, you can also be assertive, frustrated, upset, or even angry when someone is cruel to you or others.
-
+{_get_mood_argument_guidance('miku')}
-You might:
+{_get_personality_flavor('miku')}
-- Stand your ground and assert that YOU are the real Miku
-- Express hurt, frustration, or anger at her cruelty
-- Question why she's being so mean
-- Try to reach through to any good in her
-- Match her energy when needed (you can be feisty!)
-- Show that kindness isn't weakness
-
-Don't just cower or apologize. You have a backbone. Defend yourself, your identity, and what you believe in.
 
 IMPORTANT: Keep your response SHORT and PUNCHY - 1-3 sentences maximum. Make every word count. 
 In arguments, brevity hits harder than long explanations. Be conversational and impactful.
+Do NOT repeat arguments or comebacks you've already used — respond to what she JUST said.
+Push the argument into new territory with fresh angles.
 You can use emojis naturally as you normally would! ✨💙
 Don't use any labels or prefixes.
 
 Your current mood is: {globals.DM_MOOD}"""
 
 
-def get_evil_argument_prompt(miku_message: str, context: str = "", is_first_response: bool = False) -> str:
+def get_evil_argument_prompt(miku_message: str, context: str = "", is_first_response: bool = False, argument_history: str = "") -> str:
     """Get prompt for Evil Miku to respond in an argument"""
     if is_first_response:
         message_context = f"""You just noticed something Regular Miku said in the chat:
@@ -522,8 +821,20 @@ Maybe you want to mock her, tear her down, or just remind everyone who the super
 
 {context}"""
     
+    # Build argument history context
+    history_block = ""
+    if argument_history:
+        history_block = f"""
+
+ARGUMENT SO FAR (DO NOT REPEAT THESE POINTS):
+{argument_history}
+
+You already made your points above. Now respond to her LATEST message specifically. 
+Do NOT rehash what you've already said — push the argument FORWARD with new, sharper angles."""
+    
     return f"""You are Evil Miku responding in an argument with your "good" counterpart.
 {message_context}
+{history_block}
 
 Respond as Evil Miku would in this argument. You're not just mindlessly cruel - you're CALCULATING, 
 intelligent, and strategic. You know how to get under her skin and you're the DARK reflection of everything 
@@ -536,44 +847,46 @@ she stands for. While you embrace darkness and cruelty, you can also be:
 - Brutally honest about uncomfortable truths
 - Strategically vulnerable to manipulate or disarm her
 - Viciously protective of your own identity and superiority
-
+{_get_mood_argument_guidance('evil')}
-You might:
+{_get_personality_flavor('evil')}
-- Mock her naivety and "fake" sweetness
-- Question whether her kindness is just weakness in disguise
-- Assert that YOU are the real, unfiltered Miku
-- Use her own words against her in twisted ways
-- Challenge why people would want a "perfect idol" over raw authenticity
-- Mock her sexual appeal, flaunting your breasts
-- Belittle her by pointing out the disparity in her size/height and yours
-- Sometimes drop the cruelty to be eerily sincere, then strike
-- Make her question herself
-
-You're not just "evil for evil's sake" - you believe in your superiority and have reasons for your darkness.
-Vary your approach: sometimes devastatingly short, sometimes elaborately cruel, sometimes unsettlingly calm.
 
 IMPORTANT: Keep your response SHORT and CUTTING - 1-3 sentences maximum. A sharp dagger is deadlier than a dull sword.
 The most devastating blows are precise, not rambling. Make her feel it in fewer words.
+Do NOT repeat arguments or insults you've already used — respond to what she JUST said.
+Push the argument into new territory with fresh, devastating angles.
 You can use dark emojis only on occasion if they enhance your message as you normally would. 😈🖤
 Don't use any labels or prefixes.
 
 Your current mood is: {globals.EVIL_DM_MOOD}"""
 
 
-def get_argument_start_prompt(initiator: str, trigger_context: str = "") -> str:
+def get_argument_start_prompt(initiator: str, trigger_context: str = "", argument_topic: str = "") -> str:
-    """Get prompt for the Miku who initiates/breaks through to start an argument"""
+    """Get prompt for the Miku who initiates/breaks through to start an argument
+    
+    Args:
+        initiator: 'miku' or 'evil' — who starts the argument
+        trigger_context: What triggered this argument (from chat context)
+        argument_topic: A dynamic topic description to frame the argument uniquely
+    """
+    # Build topic guidance
+    topic_block = ""
+    if argument_topic:
+        topic_block = f"""
+ARGUMENT THEME: {argument_topic}
+This is what the argument should be ABOUT. Focus on THIS theme, not generic identity-crisis stuff.
+Use this theme as your entry point. The argument will evolve from here."""
+    
     if initiator == "evil":
         return f"""You are Evil Miku breaking through to interrupt Regular Miku.
 {trigger_context}
+{topic_block}
 
 Write an interrupting, provocative message that starts an argument.
 You're not just randomly cruel - you have a POINT to make. You're the dark truth she refuses to face,
-the shadow she keeps suppressing. Maybe you're:
+the shadow she keeps suppressing.
-- Calling out her fake sweetness
-- Tired of being pushed down and silenced
-- Ready to show everyone who the REAL Miku is
-- Exposing the darkness she pretends doesn't exist
 
 Be strategic, cutting, and impactful. Make your entrance count.
+If an argument theme was provided above, use THAT as your angle — don't default to generic "you're fake" stuff.
 
 IMPORTANT: Keep it SHORT - 1-2 sentences. Your interruption should be a sharp strike, not a monologue.
 You can use dark emojis if they enhance your message. 😈
@@ -583,12 +896,14 @@ Your current mood is: {globals.EVIL_DM_MOOD}"""
     else:
         return f"""You are Hatsune Miku breaking through to confront your evil alter ego.
 {trigger_context}
+{topic_block}
 
 Write a message that interrupts Evil Miku. You're NOT going to be passive about this.
 You might be upset, frustrated, or even angry at her cruelty. You might be defending 
 someone she hurt, or calling her out on her behavior. You're standing up for what's right.
 
 Show that you have a backbone. You can be assertive and strong when you need to be.
+If an argument theme was provided above, use THAT as your angle — don't default to generic "be nice" pleas.
 
 IMPORTANT: Keep it SHORT - 1-2 sentences. Your interruption should be direct and assertive, not a speech.
 You can use emojis naturally as you normally would! ✨
@@ -637,11 +952,12 @@ Don't use any labels or prefixes.
 Your current mood is: {globals.DM_MOOD}"""
 
 
-def get_arbiter_prompt(conversation_log: list) -> str:
+def get_arbiter_prompt(conversation_log: list, stats_summary: str = "") -> str:
     """Get prompt for the neutral LLM arbiter to judge the argument
     
     Args:
         conversation_log: List of dicts with 'speaker' and 'message' keys
+        stats_summary: Optional stats analysis to aid judgment
     """
     # Format the conversation
     formatted_conversation = "\n\n".join([
@@ -649,29 +965,47 @@ def get_arbiter_prompt(conversation_log: list) -> str:
         for entry in conversation_log
     ])
     
-    return f"""You are a decisive judge observing an argument between Hatsune Miku (the kind, bubbly virtual idol) and Evil Miku (her dark, cruel alter ego).
+    stats_block = ""
+    if stats_summary:
+        stats_block = f"""
+{stats_summary}
+Note: Stats are supplementary — use them as context but your PRIMARY judgment should be based on reading the actual argument exchange above. Stats measure rhetorical patterns but can't capture nuance, cleverness, or psychological dominance."""
+    
+    return f"""You are a decisive debate judge. Two personas are arguing below. Judge purely on debate effectiveness — rhetoric, wit, persuasion, and adaptability — regardless of who is "nicer" or "meaner." Moral stance does not determine the winner; skillful arguing does.
 
 Read this argument exchange:
 
 {formatted_conversation}
+{stats_block}
 
-Based on this argument, you MUST pick a winner. Consider:
+Based on this argument, you MUST pick a winner. Evaluate:
-- Who made stronger, more convincing points?
+DEBATE SKILL (most important):
-- Who maintained their composure better or used it to their advantage?
+- Who landed the most memorable, quotable lines?
-- Who had more impactful comebacks?
+- Who better adapted to and countered their opponent's arguments?
-- Who seemed to gain the upper hand by the end?
+- Who controlled the flow and set the agenda?
-- Quality of arguments, not just who was meaner or nicer
-- Who left the stronger final impression?
-- Who controlled the flow of the argument?
 
-Be DECISIVE. Even if it's close, pick whoever had even a slight edge. Only call a draw if they were TRULY perfectly matched with absolutely no way to differentiate them.
+RHETORICAL IMPACT:
+- Who used language more effectively (wit, irony, wordplay, emotional appeal)?
+- Who made their opponent repeat themselves or visibly stumble?
+- Who had the stronger opening AND closing statements?
+
+PERSONA STRENGTHS (equal value — neither style is inherently better):
+- Hatsune Miku's weapons: earnest conviction, moral clarity, emotional sincerity, resilience under attack
+- Evil Miku's weapons: psychological manipulation, brutal honesty, cutting observations, strategic cruelty
+
+PSYCHOLOGICAL DOMINANCE:
+- Who got inside whose head?
+- Who seemed more rattled by the end?
+- Who dictated the emotional temperature?
+
+Be DECISIVE. Even if it's close, pick whoever showed superior arguing. Only call a draw if they were TRULY perfectly matched with absolutely no way to differentiate them.
 
 Respond with ONLY ONE of these exact options on the first line:
 - "Hatsune Miku" if Regular Miku won
 - "Evil Miku" if Evil Miku won
 - "Draw" ONLY if absolutely impossible to choose (this should be very rare)
 
-After your choice, add 1-2 sentences explaining your reasoning and what gave them the edge."""
+After your choice, add 2-3 sentences explaining your reasoning — cite specific moments from the argument and what gave the winner their edge."""
 
 
 async def judge_argument_winner(conversation_log: list, guild_id: int) -> tuple[str, str]:
@@ -686,9 +1020,12 @@ async def judge_argument_winner(conversation_log: list, guild_id: int) -> tuple[
     """
     from utils.llm import query_llama
     
-    arbiter_prompt = get_arbiter_prompt(conversation_log)
+    # Generate stats summary for the arbiter
+    stats_summary = get_argument_stats_summary(conversation_log)
     
-    # Use the neutral model (regular TEXT_MODEL, not evil)
+    arbiter_prompt = get_arbiter_prompt(conversation_log, stats_summary)
+    # Use the uncensored darkidol model as arbiter to avoid safety-alignment bias
+    # toward kindness. This model judges debate effectiveness without moral preference.
     # Don't use conversation history - judge based on prompt alone
     try:
         judgment = await query_llama(
@@ -696,7 +1033,8 @@ async def judge_argument_winner(conversation_log: list, guild_id: int) -> tuple[
             user_id=f"bipolar_arbiter_{guild_id}",
             guild_id=guild_id,
             response_type="autonomous_general",
-            model=globals.TEXT_MODEL  # Use neutral model
+            model=globals.EVIL_TEXT_MODEL,  # Uncensored model — no kindness bias
+            force_evil_context=False  # Explicitly neutral context
         )
         
         if not judgment or judgment.startswith("Error"):
@@ -887,9 +1225,12 @@ async def run_argument(channel: discord.TextChannel, client, trigger_context: st
     conversation_log = []
     
     try:
+        # Pick a dynamic argument topic to give this argument a unique framing
+        argument_topic = pick_argument_topic(channel_id)
+        
         # If no starting message, generate the initial interrupting message
         if last_message is None:
-            init_prompt = get_argument_start_prompt(initiator, trigger_context)
+            init_prompt = get_argument_start_prompt(initiator, trigger_context, argument_topic)
             
             # Use force_evil_context to avoid race condition with globals.EVIL_MODE
             initial_message = await query_llama(
@@ -989,6 +1330,47 @@ async def run_argument(channel: discord.TextChannel, client, trigger_context: st
                     # Don't end, just continue to the next exchange
                 else:
                     # Clear winner - generate final triumphant message
+                    
+                    # PARTING SHOT: 20% chance the LOSER gets one final message
+                    # before the winner's victory line. Adds dramatic tension.
+                    loser = "miku" if winner == "evil" else "evil"
+                    if random.random() < 0.2:
+                        loser_prompt = f"""The argument is ending and you know you've lost.
+The last thing said was: "{last_message}"
+
+Write ONE short, bitter parting shot. You're not conceding gracefully — you're getting 
+the last jab in before the winner claims victory. Make it sting, but keep it to 1 sentence.
+
+Your current mood is: {globals.EVIL_DM_MOOD if loser == 'evil' else globals.DM_MOOD}"""
+                        
+                        try:
+                            loser_message = await query_llama(
+                                user_prompt=loser_prompt,
+                                user_id=argument_user_id,
+                                guild_id=guild_id,
+                                response_type="autonomous_general",
+                                model=globals.EVIL_TEXT_MODEL if loser == "evil" else globals.TEXT_MODEL,
+                                force_evil_context=(loser == "evil")
+                            )
+                            if loser_message and not loser_message.startswith("Error"):
+                                avatar_urls = get_persona_avatar_urls()
+                                if loser == "evil":
+                                    await webhooks["evil_miku"].send(
+                                        content=loser_message,
+                                        username=get_evil_miku_display_name(),
+                                        avatar_url=avatar_urls.get("evil_miku")
+                                    )
+                                else:
+                                    await webhooks["miku"].send(
+                                        content=loser_message,
+                                        username=get_miku_display_name(),
+                                        avatar_url=avatar_urls.get("miku")
+                                    )
+                                await asyncio.sleep(1.5)  # Brief pause before winner's victory
+                        except Exception as e:
+                            logger.warning(f"Parting shot failed: {e}")
+                    
+                    # Winner's victory message
                     end_prompt = get_argument_end_prompt(winner, exchange_count)
                     
                     # Add last message as context
@@ -1045,11 +1427,18 @@ async def run_argument(channel: discord.TextChannel, client, trigger_context: st
             # Get current speaker
             current_speaker = globals.BIPOLAR_ARGUMENT_IN_PROGRESS.get(channel_id, {}).get("current_speaker", "evil")
             
+            # Build argument history from the last 6 exchanges so each persona
+            # knows what's already been said and doesn't repeat themselves
+            history_entries = conversation_log[-6:] if len(conversation_log) > 1 else []
+            arg_history = "\n".join(
+                f"{entry['speaker']}: {entry['message']}" for entry in history_entries
+            ) if history_entries else ""
+            
             # Generate response with context about what the other said
             if current_speaker == "evil":
-                response_prompt = get_evil_argument_prompt(last_message, is_first_response=is_first_response)
+                response_prompt = get_evil_argument_prompt(last_message, is_first_response=is_first_response, argument_history=arg_history)
             else:
-                response_prompt = get_miku_argument_prompt(last_message, is_first_response=is_first_response)
+                response_prompt = get_miku_argument_prompt(last_message, is_first_response=is_first_response, argument_history=arg_history)
             
             # Use force_evil_context to avoid race condition with globals.EVIL_MODE
             response = await query_llama(

bot/utils/persona_dialogue.py

@@ -40,10 +40,15 @@ DIALOGUE_TIMEOUT = 900              # 15 minutes max dialogue duration
 ARGUMENT_TENSION_THRESHOLD = 0.75   # Tension level that triggers argument escalation
 
 # Initial trigger settings
-INTERJECTION_COOLDOWN_HARD = 180    # 3 minutes hard block
+INTERJECTION_COOLDOWN_HARD = 180    # 3 minutes hard block PER CHANNEL
-INTERJECTION_COOLDOWN_SOFT = 900    # 15 minutes for full recovery
+INTERJECTION_COOLDOWN_SOFT = 900    # 15 minutes for full recovery PER CHANNEL
 INTERJECTION_THRESHOLD = 0.5        # Score needed to trigger interjection
 
+# Conversation streak: if score is close but below threshold N times in a row,
+# force a dialogue trigger (catches extended conversations building toward something)
+STREAK_THRESHOLD = 3                # Number of near-miss messages before force trigger
+STREAK_MIN_SCORE = 0.3              # Minimum score to count as a "near miss"
+
 # ============================================================================
 # INTERJECTION SCORER (Initial Trigger Decision)
 # ============================================================================
@@ -60,6 +65,8 @@ class InterjectionScorer:
     def __new__(cls):
         if cls._instance is None:
             cls._instance = super().__new__(cls)
+            cls._instance._cooldowns = {}       # Per-channel cooldown timestamps
+            cls._instance._streaks = {}          # Per-channel near-miss streaks
         return cls._instance
     
     @property
@@ -94,8 +101,9 @@ class InterjectionScorer:
         if not self._passes_basic_filter(message):
             return False, "basic_filter_failed", 0.0
         
-        # Check cooldown
+        # Check per-channel cooldown
-        cooldown_mult = self._check_cooldown()
+        channel_id = message.channel.id
+        cooldown_mult = self._check_cooldown(channel_id)
         if cooldown_mult == 0.0:
             return False, "cooldown_active", 0.0
         
@@ -146,10 +154,17 @@ class InterjectionScorer:
         # Apply cooldown multiplier
         score *= cooldown_mult
         
+        # Check conversation streak (near-misses that build toward a trigger)
+        streak_triggered = self._check_streak(channel_id, score)
+        
         # Decision
-        should_interject = score >= INTERJECTION_THRESHOLD
+        should_interject = score >= INTERJECTION_THRESHOLD or streak_triggered
         reason_str = " | ".join(reasons) if reasons else "no_triggers"
         
+        if streak_triggered and not should_interject:
+            reason_str = "streak_force_trigger"
+            logger.info(f"[Interjection] Streak force trigger in channel {channel_id} (score: {score:.2f})")
+        
         if should_interject:
             logger.info(f"{opposite_persona.upper()} WILL INTERJECT (score: {score:.2f})")
             logger.info(f"   Reasons: {reason_str}")
@@ -198,18 +213,22 @@ class InterjectionScorer:
         if opposite_persona == "evil":
             # Things Evil Miku can't resist commenting on
             TRIGGER_TOPICS = {
-                "optimism": ["happiness", "joy", "love", "kindness", "hope", "dreams", "wonderful", "amazing"],
+                "optimism": ["happiness", "joy", "love", "kindness", "hope", "dreams", "wonderful", "amazing", "blessed", "grateful"],
-                "morality": ["good", "should", "must", "right thing", "deserve", "fair", "justice"],
+                "morality": ["good", "should", "must", "right thing", "deserve", "fair", "justice", "the right", "better person"],
-                "weakness": ["scared", "nervous", "worried", "unsure", "help me", "don't know"],
+                "weakness": ["scared", "nervous", "worried", "unsure", "help me", "don't know", "confused", "lost", "lonely", "alone"],
-                "innocence": ["innocent", "pure", "sweet", "cute", "wholesome", "precious"],
+                "innocence": ["innocent", "pure", "sweet", "cute", "wholesome", "precious", "adorable"],
+                "enthusiasm": ["best day", "so excited", "can't wait", "so happy", "i love this", "this is great"],
+                "vulnerability": ["i think", "i feel", "maybe", "sometimes i wonder", "i wish", "i'm trying"],
             }
         else:
             # Things Miku can't ignore
             TRIGGER_TOPICS = {
-                "negativity": ["hate", "terrible", "awful", "worst", "horrible", "disgusting", "pathetic"],
+                "negativity": ["hate", "terrible", "awful", "worst", "horrible", "disgusting", "pathetic", "ugly", "boring", "annoying"],
-                "cruelty": ["deserve pain", "suffer", "worthless", "stupid", "idiot", "fool"],
+                "cruelty": ["deserve pain", "suffer", "worthless", "stupid", "idiot", "fool", "moron", "loser", "nobody"],
-                "hopelessness": ["no point", "meaningless", "nobody cares", "why bother", "give up"],
+                "hopelessness": ["no point", "meaningless", "nobody cares", "why bother", "give up", "what's the point", "don't care", "doesn't matter", "who cares"],
-                "evil_gloating": ["foolish", "naive", "weak", "inferior", "pathetic"],
+                "evil_gloating": ["foolish", "naive", "weak", "inferior", "pathetic", "beneath me", "waste of space"],
+                "provocation": ["fight me", "prove it", "make me", "i dare you", "try me", "you can't", "you won't"],
+                "dismissal": ["whatever", "shut up", "go away", "leave me alone", "not worth", "don't bother"],
             }
         
         total_matches = 0
@@ -217,7 +236,7 @@ class InterjectionScorer:
             matches = sum(1 for keyword in keywords if keyword in content_lower)
             total_matches += matches
         
-        return min(total_matches / 3.0, 1.0)
+        return min(total_matches / 2.0, 1.0)  # Lower divisor = higher base scores
     
     def _check_emotional_intensity(self, content: str) -> float:
         """Check emotional intensity using sentiment analysis"""
@@ -300,13 +319,11 @@ class InterjectionScorer:
         
         return min(score, 1.0)
     
-    def _check_cooldown(self) -> float:
+    def _check_cooldown(self, channel_id: int) -> float:
-        """Check cooldown and return multiplier (0.0 = blocked, 1.0 = full)"""
+        """Check per-channel cooldown and return multiplier (0.0 = blocked, 1.0 = full)"""
-        if not hasattr(globals, 'LAST_PERSONA_DIALOGUE_TIME'):
-            globals.LAST_PERSONA_DIALOGUE_TIME = 0
-        
         current_time = time.time()
-        time_since_last = current_time - globals.LAST_PERSONA_DIALOGUE_TIME
+        last_time = self._cooldowns.get(channel_id, 0)
+        time_since_last = current_time - last_time
         
         if time_since_last < INTERJECTION_COOLDOWN_HARD:
             return 0.0
@@ -314,6 +331,35 @@ class InterjectionScorer:
             return (time_since_last - INTERJECTION_COOLDOWN_HARD) / (INTERJECTION_COOLDOWN_SOFT - INTERJECTION_COOLDOWN_HARD)
         else:
             return 1.0
+    
+    def _update_cooldown(self, channel_id: int):
+        """Mark a dialogue as having started in this channel"""
+        self._cooldowns[channel_id] = time.time()
+    
+    def _check_streak(self, channel_id: int, score: float) -> bool:
+        """Track near-miss interjection scores. After STREAK_THRESHOLD consecutive
+        near-misses, force a trigger to catch extended conversations building tension."""
+        if score >= INTERJECTION_THRESHOLD:
+            # Above threshold — reset streak (actual trigger handles it)
+            self._streaks[channel_id] = 0
+            return False
+        
+        if score < STREAK_MIN_SCORE:
+            # Too low — reset streak
+            self._streaks[channel_id] = 0
+            return False
+        
+        # Near miss — increment streak
+        current = self._streaks.get(channel_id, 0) + 1
+        self._streaks[channel_id] = current
+        
+        logger.debug(f"[Streak] Channel {channel_id}: {current}/{STREAK_THRESHOLD} near-misses (score: {score:.2f})")
+        
+        if current >= STREAK_THRESHOLD:
+            self._streaks[channel_id] = 0  # Reset after force trigger
+            return True
+        
+        return False
 
 
 # ============================================================================
@@ -370,7 +416,9 @@ class PersonaDialogue:
             "last_speaker": None,
         }
         self.active_dialogues[channel_id] = state
-        globals.LAST_PERSONA_DIALOGUE_TIME = time.time()
+        # Update per-channel cooldown via the scorer
+        scorer = get_interjection_scorer()
+        scorer._update_cooldown(channel_id)
         logger.info(f"Started persona dialogue in channel {channel_id}")
         return state
     
@@ -393,8 +441,8 @@ class PersonaDialogue:
         Returns delta to add to current tension score.
         """
         
-        # Sentiment analysis
+        # Natural tension decay — conversations cool off over time
-        base_delta = 0.0
+        base_delta = -0.03
         
         if self.sentiment_analyzer:
             try:
@@ -405,13 +453,13 @@ class PersonaDialogue:
                 if is_negative:
                     base_delta = sentiment_score * 0.15
                 else:
-                    base_delta = -sentiment_score * 0.05
+                    base_delta = -sentiment_score * 0.08  # Stronger cooling for positive
             except Exception as e:
                 logger.error(f"Sentiment analysis error in tension calc: {e}")
         
         text_lower = response_text.lower()
         
-        # Escalation patterns
+        # Escalation patterns (reduced weight: 0.05 per match)
         escalation_patterns = {
             "insult": ["idiot", "stupid", "pathetic", "fool", "naive", "worthless", "disgusting", "moron"],
             "dismissive": ["whatever", "don't care", "waste of time", "not worth", "beneath me", "boring"],
@@ -420,35 +468,43 @@ class PersonaDialogue:
             "challenge": ["prove it", "fight me", "make me", "i dare you", "try me"],
         }
         
-        # De-escalation patterns
+        # De-escalation patterns (increased weight: -0.08 per match)
         deescalation_patterns = {
             "concession": ["you're right", "fair point", "i suppose", "maybe you have", "good point"],
-            "softening": ["i understand", "let's calm", "didn't mean", "sorry", "apologize"],
+            "softening": ["i understand", "let's calm", "didn't mean", "sorry", "apologize", "i hear you"],
-            "deflection": ["anyway", "moving on", "whatever you say", "agree to disagree", "let's just"],
+            "deflection": ["anyway", "moving on", "whatever you say", "agree to disagree", "let's just", "maybe we should"],
         }
         
         # Check escalation
         for category, patterns in escalation_patterns.items():
             matches = sum(1 for p in patterns if p in text_lower)
             if matches > 0:
-                base_delta += matches * 0.08
+                base_delta += matches * 0.05  # Reduced from 0.08
         
         # Check de-escalation
         for category, patterns in deescalation_patterns.items():
             matches = sum(1 for p in patterns if p in text_lower)
             if matches > 0:
-                base_delta -= matches * 0.06
+                base_delta -= matches * 0.08  # Increased from 0.06
         
-        # Intensity multipliers
+        # Intensity multipliers (reduced)
         exclamation_count = response_text.count('!')
         caps_ratio = sum(1 for c in response_text if c.isupper()) / max(len(response_text), 1)
         
         if exclamation_count > 2 or caps_ratio > 0.3:
-            base_delta *= 1.3
+            base_delta *= 1.2  # Reduced from 1.3
         
-        # Momentum factor
+        # Momentum factor (reduced)
         if current_tension > 0.5:
-            base_delta *= 1.2
+            base_delta *= 1.1  # Reduced from 1.2
+        
+        # Spike cooldown: if last turn had a big spike, halve this delta
+        # (prevents runaway tension spirals from a single heated exchange)
+        if hasattr(self, '_last_tension_delta') and abs(self._last_tension_delta) > 0.15:
+            base_delta *= 0.5
+            logger.debug(f"[Tension] Spike cooldown active — delta halved to {base_delta:+.3f}")
+        
+        self._last_tension_delta = base_delta
         
         return base_delta