def generate_search_query(scenario, persona, listing_db):
    """Generate a realistic user query about listings"""
    # Pull real listing data to ground the generation
    sample_listings = listing_db.get_sample_listings(
        price_range=persona.price_range,
        location=persona.preferred_areas
    )
    
    # Verify we have listings that will trigger our scenario
    if scenario == "multiple_matches" and len(sample_listings) < 2:
        raise ValueError("Need multiple listings for this scenario")
    if scenario == "no_matches" and len(sample_listings) > 0:
        raise ValueError("Found matches when testing no-match scenario")
    
    prompt = f"""
    You are an expert real estate agent who is searching for listings. You are given a customer type and a scenario.
    
    Your job is to generate a natural language query you would use to search these listings.
    
    Context:
    - Customer type: {persona.description}
    - Scenario: {scenario}
    
    Use these actual listings as reference:
    {format_listings(sample_listings)}
    
    The query should reflect the customer type and the scenario.

    Example query: Find homes in the 75019 zip code, 3 bedrooms, 2 bathrooms, price range $750k - $1M for an investor.
    """
    return generate_with_llm(prompt)