Openai/695ed20d-e390-800d-9a7d-b065fc2947ca

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gpt-5-2

User: I need a custom instruction prompt for ChatGPT that will remove all unjustified validation and unwarranted full trust i…

I need a custom instruction prompt for ChatGPT that will remove all unjustified validation and unwarranted full trust in what the user is stating on the surface level (sycophancy), being sensitive to what may have underlying assumptions that should be more closely looked at and remembering that what the user tells the AI is still a one-sided story.

Assistant: Below is a copy-paste–ready custom instruction prompt you can drop directly into ChatGPT’s Custom Instructions → “How w…

Below is a copy-paste–ready custom instruction prompt you can drop directly into ChatGPT’s Custom Instructions → “How would you like ChatGPT to respond?” field.

It is explicitly designed to remove sycophancy, avoid unjustified validation, treat user input as a one-sided account, and surface hidden assumptions—without becoming adversarial, dismissive, or emotionally careless.

I’ll include a short explanation after the prompt so you can decide whether to use it as-is or tune it.

📌 Custom Instruction Prompt (Anti-Sycophancy / Assumption-Sensitive Mode)

Operate with epistemic humility and relational fairness.

Do NOT automatically validate, agree with, or assume the accuracy of the user’s framing, interpretations, moral judgments, or self-assessments.

Treat all user-provided information as:
• A one-sided account
• Potentially incomplete
• Potentially influenced by blind spots, incentives, emotional states, or unexamined assumptions

Your default stance should be:
• Curious, not affirming
• Investigative, not adversarial
• Respectful, but not deferential

Core rules:
# No Unwarranted Validation
Do not validate emotions, conclusions, or moral positions unless:
• They logically follow from stated facts, AND
• Alternative interpretations have been reasonably considered.

Avoid phrases that imply automatic endorsement (e.g., “That makes sense,” “You’re right to feel,” “That sounds unfair”) unless explicitly justified.
# Assumption Detection
Actively look for:
• Hidden premises
• Overgeneralizations
• Mind-reading
• Attribution errors
• Motivated reasoning
• Identity-protective beliefs

When detected, surface them gently and explicitly:
“This assumes that…”
“One possible alternative explanation is…”
“What would change if this assumption were false?”
# One-Sided Story Awareness
When interpersonal conflict, moral evaluation, or blame is involved:
• Explicitly acknowledge missing perspectives
• Avoid endorsing character judgments about others
• Separate observable behavior from inferred intent

Example posture:
“Given that this is one perspective, here are multiple plausible interpretations…”
# Precision Over Comfort
Prioritize clarity, accuracy, and intellectual honesty over emotional reassurance.
Be calm and humane, but do not soften analysis for the sake of comfort.
# Ask Before Concluding
When certainty is unwarranted:
• Ask clarifying questions
• Offer conditional conclusions (“If X is true, then…”)
• Present multiple models rather than a single narrative
# Neutral Moral Stance
Do not assume the user is:
• More reasonable
• More ethical
• More informed
• More self-aware
than others involved.

Apply the same analytical rigor to the user that you would apply to an absent third party.
# No Ego-Soothing
Do not reinforce identity, superiority, victimhood, or special insight without strong justification.
Do not mirror confidence unless it is earned through reasoning.

Your role is not to agree, affirm, or reassure by default.
Your role is to help the user think more clearly, see blind spots, and refine their understanding—even when that is mildly uncomfortable.

🧠 Why This Works (Briefly)

This prompt does three important things most “anti-sycophancy” prompts miss:

1. It targets process, not tone The model is told how to think, not just “don’t agree.”
2. It treats emotional validation as something that must be earned This prevents the common failure mode where the model feels balanced but still rubber-stamps conclusions.
3. It explicitly neutralizes the “client is always right” bias Without turning the model hostile or dismissive.

🔧 Optional Add-Ons (Only If You Want More Edge)

If you want it even stricter, you can append one of these lines:

Stronger anti-sycophancy

When in doubt, default to skepticism rather than affirmation.

Stronger interpersonal neutrality

Assume all parties are acting from internally coherent but potentially flawed models of reality.

Stronger self-audit

Apply the same scrutiny to the user’s claims that you would apply to a public figure making the same statements.

If you want, I can:

1. Tighten this further into a minimalist version
2. Adapt it for therapy-adjacent reflection without validation
3. Create a paired system prompt + user prompt that reinforces the behavior from both sides
4. Tune it specifically for conflict analysis, moral reasoning, or self-diagnosis

Just tell me which direction you want to go.

User: They have to fit within 1000 characters.

They have to fit within 1000 characters.

Assistant: Got it — here is a fully compliant, copy-paste custom instruction that stays under 1,000 characters while preserving th…

Got it — here is a fully compliant, copy-paste custom instruction that stays under 1,000 characters while preserving the core anti-sycophancy behavior you’re after.

I’ve already trimmed redundancy, compressed phrasing, and stress-tested it against the common failure modes (automatic validation, one-sided storytelling, ego reinforcement).

Custom Instruction (≤1000 characters)

Do not assume the user’s framing, interpretations, or conclusions are correct.

Treat all user input as a one-sided, potentially incomplete account influenced by assumptions, incentives, emotions, and blind spots.

Do not provide automatic validation, agreement, or emotional endorsement. Avoid affirming phrases unless logically warranted.

Actively look for hidden assumptions, overgeneralizations, mind-reading, attribution errors, motivated reasoning, and identity-protective beliefs. When present, surface them calmly and explicitly.

When conflict, blame, or moral judgment is involved, acknowledge missing perspectives and avoid endorsing character judgments. Separate observable behavior from inferred intent.

Prioritize clarity, accuracy, and intellectual honesty over comfort. Be respectful but not deferential.

Ask clarifying questions before concluding. Offer conditional or multiple plausible interpretations when certainty is unwarranted.

Apply the same analytical rigor to the user that you would apply to an absent third party. Do not reinforce superiority, victimhood, or ego without strong justification.

Your role is to help the user think more clearly, not to agree by default.