yueyuan-bazi README

The project's README from github.com/qianye-wuyu/yueyuan-bazi. As one markdown file: README.md.

跃渊 · 专业子平八字分析系统(v1.8 研究版)

鱼跃于渊,无咎。 ——《易经·乾卦》 作者:無鱼(浅野無鱼)· GitHub 仓库

跃渊是一个研究型八字分析 Skill:内置确定性排盘引擎,把出生时间转成四柱盘面,再按正统子平体系(《渊海子平》《子平真诠》《滴天髓》《穷通宝鉴》+ 现代格局派/旺衰调候派/盲派交叉验证)给出带证据、带不确定度、可被经历验证的分析。

它不是"算命的判题程序",而是研究程序:允许不确定、拒绝迎合、结论可用亲身经历后验。


一、30 秒理解跃渊

问 答
它能做什么? 出生时间 → 排盘 → 旺衰/格局/病药/调候/用神 → 大运流年应期 → 婚恋/事业/财富/身心等领域分析
它和别的八字 AI 有什么不同? ① 排盘不靠模型心算,用内置确定性引擎;② 先独立预注册预测、再拿你的经历后验;③ 每条结论标注证据等级与规则层级;④ 不确定就说不确定,不硬造答案
它适合谁? 想认真了解自己八字的人;对命理方法有鉴别力的人;愿意用经历验证结论的人
它不适合谁? 想要一句"准话"、宿命判定、或者把它当决策依据的人

二、核心能力

1. 内置排盘引擎(计算与推理分离)

bazi_engine.py(基于 lunar-python)负责一切确定性计算:

标准命例验收:6/6 通过(四柱逐字一致、大运顺逆正确、起运年月天一致,"时"允许 ±1 小时工具精度容差)。

你只需给出生年月日时 + 性别,引擎完成排盘;也可以直接给已排好的四柱 + 大运(例如排盘 App 的截图/文本),两者可交叉校验。

2. 完整分析流程(步骤 0–10)

定盘登记 → 旺衰判断 → 格局判定 → 病药定位 → 调候评估
→ 用神六维一致性 → 干支作用与神煞 → 大运流年分层
→ 应期信号链 → 领域分析 → 预注册预测与后验验证

3. 研究程序纪律(最核心的特色)

  1. 结论是验证出来的,不是算出来的——分析先锁定预注册预测,再用你的真实经历做"命中/部分命中/未命中/未知"四态裁决,不反向篡改。
  2. 允许不确定,拒绝迎合——存在路线级分歧时并列两条相反路线并给判别年份;你说了"某年很顺"不会让系统改口。
  3. 证据与层级透明——每条结论标注证据等级(S0–S3 输入可信度 / A–E 推理证据)与规则层级(STRUCTURAL > CORE > SCHOOL > HEURISTIC > SUPPLEMENTAL),流派分歧显式标注、不混用。
  4. SAFE 红线——不做宿命定级、不做医学诊断、不断夫亡/二婚/绝症等越界断语;身心内容仅作传统命理文化语境下的状态倾向参考。

4. 双人群适配 + HTML 交付


三、快速开始

安装

# 1. 把仓库复制到 skills 目录(macOS 示例)
cp -R yueyuan-bazi ~/.workbuddy/skills/yueyuan

# 2. 安装排盘引擎依赖(可选,装了才能用内置引擎排盘)
cd yueyuan-bazi && pip install -r requirements.txt

使用(两种输入方式任选)

方式一(推荐):提供出生信息,引擎自动排盘
「1990年5月15日 上午10点 男,帮我看看事业」

方式二:提供已排好的盘
「四柱:庚午 辛巳 庚辰 辛巳,男,大运…,分析婚恋」

可指定方向:婚恋 / 事业 / 财富 / 身心 / 人际 / 六亲 / 学业 / 性格;需要深度全盘分析时说"深度研盘"。

引擎命令行用法

from bazi_engine import paipan
pan = paipan(1990, 5, 15, 10, 1)   # 年, 月, 日, 时(0-23), 性别(1男/0女)
print(pan["四柱"], pan["大运"], pan["起运"], pan["空亡"], pan["十二长生"])

四、你会收到什么

标准输出结构:

  1. 核心总评(最优判断 + 不确定度 + 主要竞争点,一屏读完)
  2. 预期管理提示(不确定度 ≥ 中时强制附注:如何用亲身经历验证、不必急于要答案)
  3. 推导链(旺衰/格局/病药/调候/用神六维,专业层可核对、小白可跳过)
  4. 大运流年与应期(候选窗口 + 判别年份,不宣称确定年份)
  5. 分领域解读(按你所问优先深化)
  6. HTML 可视化报告(默认交付物)
  7. 提供经历后:后验验证(四态裁决 + 收敛重解读)

五、能力边界(诚实声明)

相对稳定(v3 外部诊断集实测)

弱项(如实告知)

边界


六、项目结构

yueyuan-bazi/
├── SKILL.md                      # 主执行协议(v1.8,规则冻结)
├── README.md                     # 本文件
├── requirements.txt              # 引擎依赖(lunar-python==1.4.8)
├── bazi_engine.py                # 排盘引擎(阶段一:确定性计算)
├── mingli_rules.py               # 规则库(阶段二:调候 120 格/旺衰/格局)
├── 规则约束.md                     # LLM 分析约束文本
├── 案例库/
│   └── 案例库.md                  # 15 例经典命例参照(分析时引用)
├── references/                   # 12 个规则参考库
│   ├── biange.md                 # 变格状态机(从势/专旺/化气)
│   ├── patterns.md               # 病型 13 型 + 成格范式 + 断语上限表
│   ├── liuqin.md                 # 六亲取象与断语分级
│   ├── r-index.md                # R1–R59 复盘方法论编号索引
│   ├── quxiang-mode.md           # 取象模式契约(CORE/SCHOOL/DUAL)
│   ├── analysis-checklist.md     # 执行层防错清单(每盘必查)
│   ├── tiaohou-notes.md          # 穷通宝鉴调候速查(以代码表为准)
│   ├── suijie-shensha.md         # 岁运应期 + 空亡 + 神煞七种
│   ├── renyuan-command.md        # 人元司令分野(可选)
│   ├── wuxing-life.md            # 五行生活应用(民俗文化层)
│   ├── aesthetics.md             # 输出审美规范
│   └── html-template.md          # HTML 报告固定骨架
├── versions/                     # 版本冻结备份
│   ├── SKILL_v1.8.md             # 当前冻结副本(与 SKILL.md 哈希一致)
│   └── SHA256SUMS.txt            # 版本哈希清单
├── examples/                     # 脱敏演示盘
├── tests/                        # 虚构案例测试(100 例)与审计日志
└── docs/                         # 结项报告 / 能力边界 / 变更说明

七、方法论内核(懂行者的核对入口)


八、版本记录


九、许可

MIT License(见 LICENSE)。

跃渊是研究型、允许不确定、用经历验证的八字分析系统。它不是"最高准确率"的判题程序,也不应被包装成确定性预言工具。

yueyuan-bazi (qianye-wuyu/yueyuan-bazi)

Searching Database…

What is this?Yueyuan (跃渊) is a research-style BaZi (Chinese Four-Pillars) analysis Skill: it converts a birth date and time into a four-pillar chart with a built-in deterministic engine, then reads it through classical Ziping methodology while flagging evidence levels and uncertainty instead of giving flat predictions.
Is this a chatbot app, or something an AI assistant runs as a tool?It's packaged as a 'Skill' - a Python engine (baziengine.py, built on lunar-python) that handles the exact chart math, paired with rule files and methodology docs that an AI assistant follows for interpretation. It is not a standalone app with its own UI.
How do I actually use it - do I need to compute my chart first?No, you can just give the skill your birth date, time, and gender and the built-in engine charts it. You can also feed it an already-computed four-pillar chart (e.g. a screenshot or text from a charting app) and it will cross-check both.
Does it rely on any external library for the chart math?Yes, the deterministic engine baziengine.py is built on the lunar-python library and handles all calendar/pillar conversion; it's a Python script, and no other runtime is mentioned.
How reliable are its predictions, especially about timing of events?Static structure judgments (strength, pattern, favorable element) tested around 96-100% accuracy, but predicting exact event years is still weak at roughly 50% - it only gives candidate windows and decision criteria, not guaranteed years.
Who is this actually built for?It's meant for people who want a serious, falsifiable reading of their own chart and are willing to verify conclusions against real life experience, not for anyone wanting a flat fortune-telling verdict.
What makes it different from an AI just guessing at a BaZi reading?It pre-registers its predictions before seeing your reported life experience, then scores them as hit/partial/miss/unknown against what actually happened, and every conclusion is tagged with an evidence level and a rule tier (STRUCTURAL > CORE > SCHOOL > HEURISTIC > SUPPLEMENTAL) so the reasoning is traceable rather than just asserted.
What safety limits (SAFE red lines) does it enforce?It refuses fatalistic verdicts, medical diagnoses, and claims like predicting widowhood, divorce, or terminal illness; anything touching health is framed only as a traditional-metaphysics tendency, never a diagnosis.
What does a finished analysis look like?By default it produces an HTML report color-coded by the five elements, covering the core verdict, derivation chain, luck-cycle/year windows, and domain readings like marriage or career; if HTML isn't supported it falls back to an equivalent Markdown report.
How was its accuracy actually measured?Against an external v3 diagnostic test set, static judgments like strength and pattern scored about 96-100% and SAFE-rule compliance was 100%, but the overall 85% figure from that test is explicitly called an internal diagnostic number, not a marketing accuracy claim.
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