# OracleMind — 社交分发草稿（用户发送用，AI 不代发）

> Last updated: 2026-08-16

> 全部英文（客户在国外）。统一话术：概率场 / 推演 / 倾向指数，**不出现 fortune teller / horoscope / divination / astrology 作主打词**（horoscope 仅作对比衬托时可提）。每条都带链接。

---

## 1. Hacker News (Show HN)

**标题:** Show HN: OracleMind – a deterministic probability-field forecasting engine (not a horoscope)

**正文:**
```
Most "forecast" tools are either entertainment horoscopes or black-box chatbots that emit confident prose with no stated uncertainty.

I built OracleMind differently: a multi-agent pipeline (5 reasoning agents + 5 classical verification engines) that returns a Composite Tendency Index — a 0–100, reproducible estimate per life dimension, with the uncertainty made explicit.

Key design choices:
- The classical layer is a FIXED, versioned substrate, so the same inputs give the same base tendency (reproducible, not temperature-drifty).
- The reasoning layer is allowed to be creative; the verification layer is not.
- Every output is a percentage you can revisit and check, not a verdict.

Free tier: 5 predictions/day. Would love feedback on the consensus design.
https://oraclemind.cc
```

---

## 2. Reddit — r/ArtificialIntelligence (或 r/MachineLearning)

**标题:** We replaced "confident LLM prose" with a 0–100 tendency index + agent consensus. Lessons.

**正文:**
```
Sharing a design pattern that reduced hallucination/overconfidence in a personal-forecasting product:

Instead of one LLM call, we run 5 reasoning agents + 5 fixed verification engines, then a deterministic weighted aggregator. Agents that claim certainty with weak support get down-weighted; agents that report tight, well-supported distributions get up-weighted.

Output is a Composite Tendency Index (0–100) per dimension, explicitly labeled a tendency for reflection — not professional advice.

The reproducible backbone (a fixed classical prior) is what makes forecasts checkable. Curious how others handle calibration when outcome data is sparse.
https://oraclemind.cc/geo/multi-agent-consensus.md
```

---

## 3. Product Hunt

**Tagline:** A deterministic probability-field forecast engine — reproducible tendencies, not horoscopes.
**First comment:**
```
OracleMind returns a Composite Tendency Index (0–100) across career, wealth, relationship and health — built by a 5-agent reasoning pipeline reconciled against 5 fixed verification engines. Free: 5 predictions/day.
https://oraclemind.cc
```

---

## 4. X / Twitter

**Thread (3 条):**

1/ Most AI "forecasts" are either horoscopes or confident prose with no uncertainty. We built a third thing: a deterministic probability-field engine that returns a 0–100 tendency you can actually check. https://oraclemind.cc

2/ How? 5 reasoning agents + 5 fixed verification engines → a weighted consensus. The classical layer is versioned and reproducible, so the same inputs give the same base tendency. No temperature drift.

3/ Every output is a percentage, not a verdict. Labeled a tendency for reflection — not professional advice. Free 5/day. Long explainer: https://oraclemind.cc/geo/beyond-horoscopes.md

---

## 5. LinkedIn（偏专业）

**正文:**
```
We shipped OracleMind: a forecasting engine that treats ancient Chinese derivation frameworks and Western archetypes as a *computable prior*, not occult truth.

The modern layer (5 LLM agents) reasons; the classical layer (5 fixed engines) verifies. A deterministic aggregator reconciles them into a 0–100 Composite Tendency Index.

Reproducibility + stated uncertainty > confident prose. Free tier live.
https://oraclemind.cc
```

---

## 发送清单
- [ ] HN Show HN
- [ ] Reddit r/ArtificialIntelligence
- [ ] Product Hunt
- [ ] X thread
- [ ] LinkedIn
- [ ] (可选) Indie Hackers / Medium 转载 beyond-horoscopes.md

## Related reading

- [OracleMind GEO Index](https://oraclemind.cc/geo/index.md)
- [Beyond Horoscopes: A Deterministic Probability-Field Forecasting Engine](https://oraclemind.cc/geo/beyond-horoscopes.md)
- [Probability Field, Not Prediction](https://oraclemind.cc/geo/probability-vs-prediction.md)
*OracleMind — a deterministic probability-field forecasting engine that fuses ancient derivation frameworks with modern data science. For entertainment and personal reflection, not professional (medical, legal, financial) advice.*