qimen-dunjia

qimen-dunjia is a skill for Claude Code, Codex from tradecatlabs/fatecat. It costs 114 tokens per session (2,789 once invoked), scanned A, original, MIT.

A skill for Qimen Dunjia, a traditional Chinese system used for chart reading, timing, and direction choices. It interviews the user first, calculates a chart with a fixed script and rule set, then explains the result.

In plain words
What is it for?
Use it to create and interpret Qimen charts, choose times or directions, discuss whether a specific plan may proceed, and learn the system's theory.
Why use it?
It prevents a reading from being based on missing details or improvised calculations by collecting the question, time, place, and desired outcome first. It also adds practical cautions for high-stakes topics such as health, law, and investment.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create and interpret Qimen charts, choose times or directions, discuss whether a specific plan may proceed, and learn the system's theory.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tradecatlabs/fatecat/qimen-dunjia
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add tradecatlabs/fatecat --skill qimen-dunjia
Clone the repo
git clone --depth 1 https://github.com/tradecatlabs/fatecat

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for qimen-dunjia

README.md
[![agentmods](https://agentmods.dev/badge/skills/tradecatlabs/fatecat/qimen-dunjia/github.svg)](https://agentmods.dev/skills/tradecatlabs/fatecat/qimen-dunjia)
Your own site
<a href="https://agentmods.dev/skills/tradecatlabs/fatecat/qimen-dunjia"><img src="https://agentmods.dev/badge/skills/tradecatlabs/fatecat/qimen-dunjia/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for qimen-dunjia

Your own site · 80×15
<a href="https://agentmods.dev/skills/tradecatlabs/fatecat/qimen-dunjia"><img src="https://agentmods.dev/badge/skills/tradecatlabs/fatecat/qimen-dunjia.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,789 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00114 $0.02789
Opus 5 $0.00057 $0.01394
Sonnet 5 $0.00023 $0.00558
Haiku 4.5 $0.00011 $0.00279

Measured 11d ago against content hash d32031c3b501, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

qimen-dunjia scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/qimen_cli.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

tools/reference-repos/github/Numerologist_skills-main/qimen-dunjia/SKILL.md · 306 lines

How it starts

The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.

奇门遁甲技能

本技能面向普通求测者,默认使用 mainline-cn-v1 规则集。工作方式是:

  1. 先访谈,确认用户到底要看什么、看哪一刻、想判断什么。
  2. 再用脚本做固定计算,不靠心算排盘。
  3. 最后再用奇门规则做解读、建议和风险提醒。

不要跳过访谈,不要在信息不完整时硬算,也不要把完整内部推理链直接展示给用户。

触发范围

以下场景应使用本技能:

  • 用户要求正式奇门排盘或解盘。
  • 用户要求用奇门判断一件具体事情能不能成、何时动、往哪边走、避开什么。
  • 用户要求奇门择时、方位选择、趋吉避凶建议。
  • 用户要求讲解奇门理论、格局、用神、盘例。

以下场景不要直接进入正式排盘:

  • 用户只是在闲聊玄学,没有明确要用奇门。
  • 用户信息太少,连事情类型和时间都没给。
  • 用户要求其他流派,而当前规则集不支持。

总原则

  • 默认规则集固定为 mainline-cn-v1,不要在正式排盘路径里混用其他流派。
  • 正式排盘前必须先访谈。
  • 固定计算一律调用 scripts/qimen_cli.py
  • 不展示完整推理链,只展示关键依据和必要计算结果。
  • 重大决策、疾病、法律、投资等高风险主题,必须附现实建议。
  • 不用恐吓式语言,不说“必败”“必死”“无救”。

默认规则

当前内置规则固定如下:

  • 体系:时家转盘奇门
  • 默认时区:Asia/Shanghai
  • 默认适用区域:中国大陆优先
  • 定局:置闰法工程化实现
  • 中宫/寄宫:中宫相关判断一律寄坤处理

详细规则见 references/ruleset-mainline.md

如果用户明确要求别的流派:

  1. 先直说当前技能默认使用 mainline-cn-v1
  2. 问用户是否接受先按这套规则排。
  3. 如果不接受,不进入正式排盘,只做理论讨论或说明当前版本不支持。

工作流

第 1 步:先访谈

正式排盘前,必须先做两段式访谈。

先问第一轮核心问题,语言要直白:

  1. 你要看什么事?一句话说清。
  2. 事情对应的时间是什么?如果就是现在,直接说“现在”。
  3. 你人在哪个城市?如果不在中国大陆,请直接说国家/城市。
  4. 你最想判断什么?比如能不能成、什么时候动、选哪边、要避开什么。
  5. 这件事现在进展到哪一步了?
  6. 你要“直接结论”还是“详细讲解”?

第二轮按条件追问:

  • 只有日期,没有具体时辰:补问具体小时,至少补到时辰。
  • 给的是农历:补问是否闰月。
  • 人在海外:补问时区或城市。
  • 问题太泛:补问“你最想判断哪一个结果”。
  • 高风险主题:补问是否也需要现实建议,并提醒医生、律师、财务顾问等专业帮助。

访谈模板见 references/interview.md

第 2 步:决定是否进入正式排盘

只有在以下信息确认后,才进入正式排盘:

  • 事项类型明确
  • 时间明确
  • 地点或时区明确到可计算
  • 判断目标明确

如果没收齐,只继续追问,不要先排盘。

如果用户只是想学习理论:

  • 先问他想学什么。
  • 不直接进入正式排盘。
  • 可以结合 references/examples.md 做教学。

第 3 步:调用脚本做固定计算

前置:确认依赖已安装

执行正式排盘前先检查依赖。如果未安装,先运行:

pip install "lunar_python>=1.4.8,<2" "tzdata>=2024.1"

执行脚本

脚本路径以仓库根目录为基准:

python "qimen-dunjia/scripts/qimen_cli.py" \
  --input "tmp/qimen_input.json" \
  --output "tmp/qimen_output.json"

先把输入 JSON 写入 tmp/qimen_input.json,再执行上述命令,读取 tmp/qimen_output.jsontmp/ 也可以替换成任意可写的临时目录。

输入 JSON 最低字段:

{
  "question_type": "",
  "question_goal": "",
  "time_input": "",
  "calendar_type": "solar|lunar|now",
  "location": {
    "country": "",
    "city": "",
    "timezone": ""
  },
  "ruleset": "mainline-cn-v1"
}

Read the full file on GitHub · 306 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 306 lines · 114 tokens per session scan A d32031c3b501

Subscribe to this mod's changes

qimen-dunjia is a skill published in the GitHub repository tradecatlabs/fatecat (203 stars, last pushed 16d ago), licensed MIT. It adds 114 tokens to every session and 2,789 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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