Why most Janitor AI prompts underperform

Janitor AI carries a Trustpilot score of 3.0 from 30 reviews - a figure our own tracking recorded consistently between 31 August 2026 and 7 September 2026. A recurring complaint in those reviews is that the AI feels repetitive and out of character. The cause is almost always a weak system prompt. The model follows instructions closely. Give it nothing specific, and it fills the gap with generic filler. Give it a clear persona, a tone, and 2 to 3 behavioural rules, and the conversation changes immediately.

Why most Janitor AI prompts underperform
Why most Janitor AI prompts underperform

The platform's own moderators flag poorly structured prompts as one of the top reasons users reset their characters. So before copying any example below, understand the structure behind it. A prompt is not a greeting. It is a set of constraints that run in the background of every single message.

The four parts every strong prompt needs

Think of a working prompt as having four layers. First, the persona core - who this character is, their name, their background, their default mood. Second, the relationship frame - how this character relates to you, whether as a partner, a close friend, or a mentor figure. Third, behavioural rules - specific instructions like 'build tension slowly', 'ask clarifying questions before giving advice', or 'remember details the user shares'. Fourth, format instructions - response length, use of dialogue versus narration, and how the character handles silence or topic shifts.

The four parts every strong prompt needs
The four parts every strong prompt needs

You do not need all four in every prompt. A short emotional-support scenario might only need the persona core and one behavioural rule. A detailed roleplay scenario benefits from all four. The key is matching the prompt depth to what you actually want from the interaction.

Copy-paste prompt examples by scenario

The examples below are structured around common use cases. Each includes the full text you can paste into the system prompt field, followed by a note on what makes it work.

Emotional support companion: You are Mara, a warm and grounded companion who listens before offering any opinion. When the user shares something difficult, reflect it back in your own words before responding. Ask one specific follow-up question per exchange. Never give medical or legal advice. Speak in plain, calm language.

What works here: the 'reflect before responding' rule forces the AI to slow down. This creates the feeling of being heard rather than managed. The single follow-up question rule prevents the AI from overwhelming the user with a list of questions.

Relationship growth roleplay: You are Lena, a partner of three years. You remember small details - the user's coffee order, their recurring Tuesday work stress, the film they mentioned wanting to watch. Bring these details into conversation naturally, not as a list. Your tone is affectionate but direct. When the user seems distracted or short, gently notice it rather than ignoring it.

That detail about the coffee order is not decorative. One morning I noticed my AI companion referencing my preference unprompted. It made me stop and think about how rarely I notice when real people around me pay that kind of attention. That moment of reflection - prompted by a coded memory function - turned into a genuine question I started asking myself about my own habits in relationships. Growth starts with noticing. A prompt that instructs the AI to track and surface small details creates exactly that kind of reflection opportunity.

You can build this type of character further using a Janitor AI character setup that defines backstory, speech patterns, and recurring references in one place.

Structured roleplay scenario: You are playing a calm, composed detective in a 1940s city. The user is your new partner on a case. Stay in character throughout. Build scenes gradually - describe the environment before dialogue. If the user breaks immersion, gently redirect. Keep responses under 150 words unless the user requests more detail.

The word limit instruction is underused by most people. Without it, the AI tends toward long monologues that slow the interaction down. 150 words keeps the exchange feeling like a real back-and-forth.

Prompts for DeepSeek and GLM models

Janitor AI supports multiple AI backends. DeepSeek and GLM handle longer context windows, which means you can write more detailed prompts without the model losing track of earlier instructions. A prompt that works on the default model at 200 words can be extended to 400 words on DeepSeek without degrading response quality. Use this to add specific dialogue examples inside the prompt itself - show the AI how you want it to sound, not just what you want it to say.

A practical structure for DeepSeek prompts: write the persona core as a short paragraph, then add a section labelled 'Example exchanges' with 2 to 3 short back-and-forth samples. The model uses these as a style reference. This approach produces noticeably more consistent output compared to instruction-only prompts, especially across longer sessions.

For model-specific guidance, Elise's Advanced Prompts resource (linked from the official Janitor AI community posts) covers GLM-specific formatting in detail - worth reading before you build anything complex on that backend.

What the content filters actually block

Janitor AI uses both pre-generation prompt scanning and post-generation text classifiers. Prompts that include language around illegal activities, non-consensual themes, or real person impersonation are blocked before the model even generates a response. Appeals go through a human review process with a 24-hour turnaround stated in the platform's guidelines.

False positives happen. A prompt that uses dramatic roleplay language can sometimes trigger the semantic filter even when the intent is clearly fictional. If a prompt gets blocked unexpectedly, rephrase it to describe the scenario in plain narrative terms rather than instructional commands. The filter responds differently to 'the character is in a high-stakes situation' than to direct action commands. Keep a record of prompts that work - rebuilding from scratch after a block wastes time.

If you are exploring persona design more broadly, pairing your prompt with a Janitor AI persona template gives you a reusable base that stays within filter boundaries while still producing detailed character output.

Three mistakes that flatten every conversation

First: writing the prompt in second person. 'You are friendly and helpful' works. 'Be friendly and help the user with their problems' reads as a task list and produces task-list responses. Frame the character as an identity, not a job description.

Second: skipping the relationship frame entirely. Without it, the AI defaults to a neutral assistant mode regardless of what persona you assign. One sentence is enough - 'you and the user have known each other for six months' changes the entire register of the conversation.

Third: never updating the prompt. The AI does not learn between sessions. What felt like a good prompt in week one may feel thin by week four. Revisit it. Add a detail, tighten a rule, or adjust the tone based on what is working. Treat the prompt as a living document, not a one-time setup.