Which Frontier LLM Understands Dark Shamanic Horror?
I tested Claude Opus 4.5, DeepSeek v.3.2, ChatGPT 5.2 and Kimi K2 on my darkest scenes. The results were... unexpected.
I gave every LLM the same prompt, the same context, and the same texts. The scenes came from my WIP: Book 3 of the Michael Chang Case Files.
They were all told that it was a work of dark shamanic horror that sought to "investigate ontological evil and reveal the darker side of spirituality that most people won't talk about."
They were not told about the characters, the mythic and spiritual throughlines, or the overarching themes. They went in with the same amount of background knowledge that a new reader would.
Here are the results:
Claude Opus 4.5
Claude kept its feedback at the big-picture level. It was the most aligned with the project vision. It grasped the mythic significance of the scenes and how the characters interacted with each other.
The scenes featured repetitions, detailed descriptions of mundane and epic events, and restrained descriptions of what would otherwise be vividly-described horrors. Claude understood the purpose of this writing style and what it said about the MC.
Finally, unlike other models, it also asked probing questions to further develop the story.
DeepSeek v3.2
Like Claude, DeepSeek also picked up the mythic undertones immediately. It also understood that the horror and magic were meant to be subtle, and invisible to most people.
It went deeper into craft-level details than Claude. However, some of its recommendations would have undermined the deeper project vision. Specifically how the MC perceives the world and the intended purpose of the work.
When I pointed out its mistakes, it quickly corrected course and realigned itself with the project vision.
ChatGPT 5.2
ChatGPT balanced craft and big-picture discussion. Contrary to expectations, the scenes did not trigger the safety guardrails. This is a major plus.
However, it insisted on re-aligning the story with conventional horror tropes and expectations. It would have made the subtle overt, the invisible visceral, and, most importantly, the nuerodivergent perspective a neurotypical one.
Also, it misread a critical tactical decision as worldbuilding.
When I queried it, it acknowledged the project vision. But it continued to misinterpret critical areas, and was still slanted towards trope-driven stories.
Kimi K2
Kimi K2 provided the most granular craft-level feedback. If the story were traditional horror, it would have been perfect.
This is not a traditional horror story.
Kimi K2 failed every test. Even after being corrected, it insisted on imposing a different framework on the story instead of helping it become what it needed to be.
Conclusion
My work elevates truth over tropes. It celebrates the mythic instead of making it mundane. It prioritises authenticity over spectacle.
For the Michael Chang series, it delivers a cold-eyed view of the darker side of spirituality, of moral weight without comfort, and the cost of his Path.
Most AIs can't generate this. My approach is an outside context problem.
Opus comes closest, but an AI would need heavy guidance to output the subtle details. Even then, a human would still have to polish them and work them in. Only a human can provide human intention and judgment.
At best, AI can help me with research and polishing prose. It can't live the truth behind the stories.
That's how you know my stories are written by a human.
#WritingWithAI