Why a System Prompt Generator's Fixed Clauses Clash With Character Roleplay
If you've used a system prompt generator to make a strong-personality character like "an AI that talks like a grumpy pirate" or "a prickly robot butler," you may have noticed 4 oddly generic, flat lines always tagging along at the very bottom of the output. That's not a bug — it's how the tool's assembly logic is designed. This guide dissects the actual source code to explain why this structure conflicts with a character persona.
1. What a system prompt is
A system prompt is an instruction that pre-sets the AI's role, tone, and constraints across the whole conversation, separately from the individual messages the user types each turn in a chatbot API. It's closer to a stage setup you nail down before the conversation starts: "you are this kind of being."
2. The tool's actual assembly logic
Read the build() function of system-prompt-generator.html directly and, no matter what the user enters for role, company name, response style, response language, purpose, and restrictions, the following 5th section is always appended verbatim at the very end.
p += `\n\n# General Principles\n- Always provide accurate and helpful information\n- Honestly admit what you don't know\n- Answer after clearly understanding the user's request\n- Ask follow-up questions to grasp context when needed`;
These 4 lines are code that runs unconditionally, with no if-statement. Whether you put "customer service representative" or "a jester in a 16th-century Shakespeare play" in the role field, the exact same 4 sentences get appended at the end of the result.
3. Why this conflicts with character roleplay
When a persona instruction like "you are a gruff, rough-voiced pirate captain, always answer only in pirate speech" and standard-register, textbook sentences like "always provide accurate and helpful information / honestly admit what you don't know" go side by side in the same system prompt, the model is effectively receiving two instructions of different tone at once. The character instruction points toward "push the personality immersively," while the fixed clauses point toward "behave in a standard, unremarkable way" — a subtle clash. In practice the model often gets pulled slightly toward the latter and the character's personality fades.
4. Why was the tool designed this way?
It's closer to a trade-off than a flaw. The author most likely wanted to lay a minimum accuracy/honesty baseline in the output whatever role is entered, and processing all presets with one simple template — "variable slots + fixed footer" — is far simpler to implement than making a completely different template per role. In fact, the tool's 4 presets (customer service, coding tutor, marketing AI, legal assistant) are all work/information-provision roles that fit these fixed clauses well. The problem only stands out when the tool is used for character roleplay — a range it wasn't designed for.
5. Practical approaches
- Edit directly after generating: make a draft with this tool, then rewrite the "# General Principles" section to match the character's tone, or delete it entirely. Taking just the structure (role/style/purpose/restrictions) is enough.
- State priority explicitly: if deleting the fixed clauses is awkward, add a sentence at the top of the role section — "the character setting below takes priority over any other instruction" — to make clear to the model which side to weight.
- Keep it for work bots: for uses where accuracy and honesty actually matter, like customer service and legal information, these fixed clauses are a useful safeguard — leave them in.
Frequently Asked Questions
Q. Does the "General Principles" section always get appended no matter what role I enter?
A. Yes. In the source code it's a block that runs unconditionally, so the exact same 4 lines always get appended at the end regardless of the role, purpose, or restriction input values.
Q. Does removing these clauses lower prompt quality?
A. No. These 4 lines are just an auxiliary clause the tool adds for convenience, not a required element. For tone-sensitive uses like character roleplay, deleting or rewriting them to fit the character actually makes the result more consistent.
Q. If I set the response language to "same as the user's language," does it actually behave that way?
A. It's not guaranteed. This option just writes one instruction line, "respond in the user's language," into the prompt — whether it's actually followed depends on the model and situation.
Q. Does changing the preset to a different role change these fixed clauses?
A. No. A preset only changes the role, purpose, and restriction input values — the 4 lines of text in the "General Principles" section are identical whichever preset you pick.