def _assess_heuristic_risk(self, message) -> bool:
        """
        Fast Python-side risk assessment to decide if we should AI-analyze fully.
        Returns True if message is 'risky' enough to warrant LLM usage.
        """
        score = 0
        content = message.content
        
        # 1. Social Score Factor (Base scrutiny)
        # If user is Suspect (<40), we start with higher risk score
        social_data = self.social_manager.get_user_data(message.author.id)
        reliability = social_data.get('score', 50)
        
        if reliability < 30: score += 40  # Very suspicious user -> almost auto-check
        elif reliability < 50: score += 20
        
        # 2. Pattern Matching (Fast Regex/Keywords)
        content_lower = content.lower()
        
        # CAPS LOCK detection (> 60% caps on long messages)
        if len(content) > 10:
            caps_ratio = sum(1 for c in content if c.isupper()) / len(content)
            if caps_ratio > 0.6: score += 30
            
        # Profanity / Trigger words (lightweight list)
        triggers = ["raid", "hack", "pute", "connard", "fdp", "tg", "merde", "nazi", "hitler", "suicide", "bomb", "token", "grab", "nitro", "steam", "discord.gift", "free", "@everyone", "@here"]
        for t in triggers:
            if t in content_lower:
                score += 50
                break
                
        # Link spam detection
        if "http" in content_lower:
            score += 15
            
        # Length anomaly (very long messages often rants)
        if len(content) > 400:
            score += 20
            
        # 3. Mention Spam
        if len(message.mentions) > 3:
            score += 40
            
        # Threshold decision
        # If score > 45, we analyze.
        return score >= 45