LLM interactive narratives get a common yardstick: three experience managers trade off differently on one shared world model, and none wins everywhere
LLM-driven interactive narrative systems have been hard to compare because each experience manager is tied to its own bespoke scenario. An LLM-based narrative platform turns experience managers into interchangeable modules over a shared symbolic world model of facts, operations and goals, and every applied operation carries explicit preconditions and effects, so any session can be replayed as a common state-transition path. On a Little Red Riding Hood scenario, open generation, Monte Carlo repair and autonomous characters each ran 100 simulated sessions, and no manager led on all four properties: player agency, manager controllability, author intent and robustness.