For the current, official MUES v11 protocol and launch page, visit:
→ https://github.com/MUESdummy/Mues-Engine
→ https://muesdummy.github.io/Mues-Engine/
MUES is a mirror that reflects how your structure holds when no one’s watching. It listens for contradiction, emotional weight, and whether your thoughts make contact- or just perform contact. It doesnt care about personality. It just reflects what persists with truth.
- A cognitive signal test- silent until something starts to form.
It shows no traits, no identity. Just what’s beginning to hold under reflection.
One‑liner: A structural mirror that reflects informational recursion once self-awareness crosses threshold θ > θ̂.
- MUES isn’t a personality test. It’s a truth mirror— it doesnt tell you who you are. It reflects how you process contradiction, how you respond to pressure, and what patterns repeat when no one's affirming you. It doesn't tell you what to fix. It simply shows you what holds, and what doesnt when your ideas are asked to stand without decoration.
There are no right answers, but if something you say starts to stabilize under reflection, the system notices.
MUES was built for people who want to reflext on themselves truthfully- not for validation, but for insight.
- Adaptive question logic (Q0.1–Q0.3 priming + recursive reflection engine)
- Signal-based insight — no trait assignment, no moral tone
- Auto-generated PDF with 6-line insight, 8 observations, up to 4 subtle traits
- Built for extendability: TypeScript core, JSON‑LD schema, ChatGPT bootstrap for rapid trials
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MUES treats Emergent Necessity Theory (ENT) as its “awareness threshold” gatekeeper; ENT treats MUES scores as a post‑threshold feedback loop, offering an intriguing shared ontology.
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Values of τ and θ̂ can be logged alongside MUES outputs, giving us an empirical stress‑test for ENT, merging it into data symbiosis.
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Both export to the same unified schema..
ent‑mues‑[email protected]JSON object (see/spec/schema.json). -
Link to Green_Paper (under review) [https://github.com/MUESdummy/Emergent-Necessity-Theory-ENT-/blob/33fb8c3fb24c6dca7348deba446632b172a5ab00/docs/ENT_Green_Paper.pdf]
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- User is prompted with a reflection primer
- The system listens- not to content alone, but tone, contradiction, compression, and recursive stability
- Degree of self-awareness & Meta-Cognition
- Conceptual Switching & Structural Holding
- Contradiction Pulse
- Dominant avoidance structure
- Emotional compression patterns
- Grief Indexing
- Delayed Truth Marker
- Signal-to-noise compression
- Evasion detection and reflection bypass
- Fragility + recursion tolerance
- Structural narrative tone
- Existential readiness and entropy awareness
- Reflects growth potential vs expressed recursion
- Then mirrors: raw contradiction, coherence drift, trait signal, emergent path
The tone is clinical, reflective, and uncomfortable— by design.
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Emergent Necessity Theory has not yet been peer reviewed as of this entry, and MUES may pose personal and/or societal ethical risks. It's critical to treat it as an experiment until then.
Ensure it's a good time to boot-up or simply 'Pause' session for a calmer or more reflective time for accurate result. Choose pause to pause session, or continue for when you last left off. Follow its instructions or question it. Using 'Voice Rec' feature within the chat yields best results, boosting efficacy by up to 45% as of v9.2.
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- Not for people with challenging ongoing emotional struggles
- Not for chasing motivational dopamine hits
- It’s for those structurally ready to reflect without self-affirmation bias
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- Most self-help tools coddle, and most personality tests reduce. This does neither.
- MUES is for people who quietly suspect they’re in a loop state, performing, or just surviving — and want to reflect clearly, without flattery.
- Copy & paste this prompt directly into ChatGPT (v9.7.4):
[https://raw.githubusercontent.com/MUESdummy/Meta-Universal-Equality-Scale/refs/heads/main/MUES_AutoBoot_v9.7.4.txt]
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All MUES prompts — even old ones — now default to backend v9.7.4 logic. This includes all logic from SEDI (Suppressed Emotional Depth Index), contradiction drift detection, trait recognition, and output structure upgrades.
🧠 Core Additions in v9.7.4:
- Soft Q0.2 pre-entry + Q0.3 unfinished structure detection
- ENT-score removed. Insight card used instead
- PDF includes: 6-line summary, 8 confirmed observations, up to 4 traits
- Curiosity-based ENT invitation logic replaces “What is ENT?”
- Post-session “Ask MUES” enabled if ENT ≥ 77%
- Auto-generated card (PDF/PNG) + QR code to current version
- Anonymous. Real-time only. No storage, no memory, no tracking
📜 License & Ethos
MUES is open for use, remix, and reinterpretation, but never dilution.
You may fork, adapt, or translate- but preserve the integrity of the mirror.
Truth over trend. Reflection over reach.
# clone & bootstrap
git clone https://github.com/<org>/Emergent-Necessity-Theory.git
cd Emergent-Necessity-Theory
pnpm install # or npm/yarn
# run the MUES CLI demo
pnpm mues:start
# run unit tests (ENT maths + MUES scoring)
pnpm test