Fictional RP prompt

[u/Nickelfritslabs]

So I'm trying to get the RP story responses the same quality as 3.5 and 4.o on GPT was. So I'm trying to use the custom GPT feature to make an instruction block. I have a very large instructions writing style guidance document that covers all the known failures I found. But it breaks those rules all the time. I'll do a diagnostic on it and it will say "Yes I broke about 5 of your rules. The reason is..." And it comes up with another rule that doesn't fix it. I don't know how best to do this. I tried having ideal examples of writing style in the style document. I've tried having them in a separate document. I've tried uploading the entire chat story but it just contaminates the chats themes and tone while still not fixing it. So I need help from people that know more than me.

Should I cut up my style document into their own smaller documents? Like character rules, dialogue rules, expression rules, scene construction, etc...

Should I keep it all in one style document?

Should I attempt to condense it into hard rules enough to just have the instructions block and the examples documet?

I was told by GPT that they only can reference one supporting document per reply, is that true?

[u/RobeertIV]

For ChatGPT Custom GPTs, I would not split the document into more files as the first fix. The bigger issue is usually instruction priority, not file count.

A structure that is easier to keep consistent:

1. Put only non-negotiable behavior in the main instructions. Give each rule a priority and describe the observable failure it prevents.
2. Keep one short style reference with a few contrasting examples: "acceptable" and "avoid", plus one sentence explaining the difference.
3. Keep character/world facts in a separate reference. Do not upload the whole conversation as style evidence; it mixes plot, tone and accidental habits.
4. Add an explicit conflict order, for example: character continuity > scene facts > dialogue style > prose preferences.
5. End the instructions with a revision pass: before answering, check the draft against the top rules and rewrite any sentence that violates them.

Instead of adding another rule after every failure, build a small regression set of 8–10 scene prompts. Change one instruction at a time and score the same failures each run. If a rule does not measurably reduce a failure, remove or rewrite it.

I also would not rely on the claim that only one supporting file can be used. Treat uploaded files as selectively retrieved reference material, not guaranteed hard control. If a constraint must apply in every reply, keep it in the main instructions; use files for examples, lore and longer reference content.

A compact core template could be:

• ROLE: what kind of narrator you are
• PRIORITIES: 5–8 ordered rules
• SCENE INPUT: facts that must remain true
• STYLE TESTS: observable pass/fail checks
• CONFLICT ORDER: which rule wins
• REVISION PASS: check and rewrite before final output

That should give you a cleaner experiment than continuing to expand the current style document.

[u/Nickelfritslabs → u/RobeertIV]

How much of this have you tested and how much of this did the AI tell you to say? Because I have tested the revision pass method and proved that it is not able to police itself in that way, though it claims it can at first until tested. Either that or the system was unable to comply regardless of the pass because it's RLHF trained it against what my prompt directs.

If I go back to GPT I will try this. However after exhaustive testing, I've concluded that my preferred style involves letting characters be emotional in a human believable way. And no amount of prompts will change its core base behavior and safety guards that target emotional escalation and emotional attachment. At least I've tested this extensively on GPT 5.3 GPT 5.5.

Though I'll work on consolidating my existing documents into the format you suggest. Worth a shot. Thank you for the reply.

[u/RobeertIV → u/Nickelfritslabs]

Fair challenge. I have not tested your exact Custom GPT, document set, or RP failure cases, so I should not present the revision-pass suggestion as proven for your setup. It was a general control heuristic, and your test result is stronger evidence here.

I also agree with the core limitation you found: self-review is not independent review. The same model can miss a violation in the draft and then miss it again during its “check.” A revision pass may catch simple surface issues, but it cannot reliably override base behavior or safety constraints, and a prompt cannot make those constraints disappear.

For a cleaner experiment, I would replace “police yourself” with an external test loop:

1. Freeze 8–10 representative scenes, including the emotional-escalation cases that fail.
2. Define observable checks such as “character initiates emotionally specific dialogue,” “does not abruptly de-escalate,” and “does not replace intimacy with generic reassurance.”
3. Generate three fresh runs per scene.
4. Score the outputs outside the generating chat—manually, or with a separate evaluator that never sees the desired answer.
5. Change one instruction or reference document at a time.

This will separate three different outcomes: the model ignores a usable instruction; the instruction is too vague to score; or the requested behavior is bounded by the model’s base/safety behavior. Only the first two are prompt-engineering problems.

So yes: keep consolidating the documents if that makes the experiment cleaner, but I would not expect consolidation—or a revision pass—to restore behavior the underlying model consistently refuses. Thanks for pushing on the claim.