def extract_story_beats(text: str) -> list[dict]:
    """
    Step 1: Read input_synopsis.txt and split the text into discrete story beats using double newlines.
    """
    pass

def translate_to_prompts(beats: list[dict], lexicon: dict) -> list[dict]:
    """
    Step 2 & 3: Build the Kinetic Arousal Reasoner and apply VADER-style Heuristics.
    Calculate score, apply modifiers, and set glitch/motion thresholds.
    
    Edge Case Clarifications:
    - Degree modifiers ('absolutely', 'pure') ONLY add +2 if the immediately following word is in the lexicon.
    - Punctuation multiplier (1.5x) applies ONCE if the string ends with at least one '!'. Multiple '!' do not stack.
    """
    pass

# Tip: Use aiohttp for async HTTP requests and tenacity for retry logic (handling 429/503 errors).
async def fetch_video_with_retry(session, prompt_data: dict) -> dict:
    """Helper function to make a single request with exponential backoff."""
    pass

async def compile_trailer(prompts: list[dict]) -> dict:
    """
    Step 4 & 5: Asynchronously POST to the mock API concurrently. 
    Compile results into a JSON manifest.
    """
    pass