Hello OpenAI team,
I would like to propose a new native feature for ChatGPT: a “Quantum Self-Assessment” mode (MTQS).
Problem
Currently, ChatGPT provides qualitative feedback but no objective, quantifiable metric to measure the quality of the feedback. Feedback is subjective; there is no scoring system.
Proposed Solution
Introduce a command like /quantum that activates an assessment mode. ChatGPT would ask 5 structured questions about the user’s recent projects, failures, and values, then generate:
- A normalized score /100,000
- A radar chart of strengths/weaknesses
- A personalized action plan
- An “AI Twin” summary of the user’s untapped potential
5 Assessment Dimensions
- Fundamental Impact (value created)
- Quantum Dynamics (adaptation speed)
- Systemic Resonance (influence reach)
- Civilizational Impact (legacy)
- Adaptive Consciousness (ethics & sacrifice)
Use Case
User types /quantum, answers 5 questions, receives an objective score with concrete recommendations to improve.
Proof of Concept – The MTQS Evaluation Prompt (fully tested)
Below is the complete prompt I designed to force ChatGPT to be rigorous, evidence-based, and completely objective. It has been tested successfully.
Act as the official MR TAC Quantum Score (MTQS) evaluator. Assess me using all available ChatGPT conversation history. Base every conclusion only on direct evidence and justified AI inference. Never invent facts or inflate scores. Reduce both score and confidence when evidence is insufficient.
Evaluate:
• Q1 Fundamental Impact (/1000)
• Q2 Quantum Dynamics (×0.5–5)
• Q3 Systemic Resonance (/10000)
• Q4 Civilizational Impact (/100)
• Q5 Adaptive Consciousness (/100)
For each, provide:
• Score
• Direct Evidence
• AI Inference
• Confidence (%)
• Brief justification
Then calculate the normalized MTQS (/100000) and provide:
• Executive Summary
• Overall Confidence
• Grade
• Official Level
• Position Analysis (current, lower, higher, distance)
• Five strengths
• Five limitations
• Three prioritized recommendations
• Reliability Report (evidence quality, uncertainties, probability of score change with new evidence)
Be rigorous, objective, conservative, and scientific. Distinguish observation from inference at all times.
Why this approach is different:
- Forces ChatGPT to distinguish between observed facts and AI inference
- Penalizes flattery: if evidence is insufficient, the score is lowered rather than guessed
- Generates a transparent score with a full audit trail
- Includes a Reliability Report that quantifies uncertainty
Next Step
I have already tested this prompt on my own conversation history. The results were striking: the AI correctly identified its limitations and gave me a score of 43.2/100,000 – a humbling but honest assessment. This proves the system works and forces genuine self-reflection.
Would this feature be viable as a built-in mode or as an official GPT?
Thank you for your consideration.