Root Cause Priority logo

Root Cause Priority

Community
dhicoc
root-cause-priority

用户面对多个相互关联的问题, 不知道先解决哪个时; 当需要区分根本原因 与表面症状时; 当问题有先后因果链需要追溯源头时。 不适用于: 只有一个简单问题的场景、问题之间没有因果关系的场景。

Overview

Publisherdhicoc
Repositorywuyun-liuqi-skills
Skill nameroot-cause-priority
Stars
52
Forks
10
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dhicoc on GitHub. Read the source before you install it.

Installation

Install the Root Cause Priority AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dhicoc/wuyun-liuqi-skills/tree/master/scripts/lib/neijing_snapshot/lingshu/root-cause-priority
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dhicoc/wuyun-liuqi-skills.git /tmp/wuyun-liuqi-skills
mkdir -p .claude/skills
cp -r /tmp/wuyun-liuqi-skills/scripts/lib/neijing_snapshot/lingshu/root-cause-priority .claude/skills/root-cause-priority
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Root Cause Priority in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Root Cause Priority on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Root Cause Priority is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

标本根结定位法

R — 原文 (Reading)

先病而后逆者治其本, 先逆而后病者治其本。 先病而后生中满者治其标, 先中满而后烦心者治其本。 病发而有余, 本而标之; 病发而不足, 标而本之。 能知六经标本者, 可以无惑于天下。

— 黄帝/岐伯, 病本第二十五、卫气第五十二


I — 方法论骨架 (Interpretation)

标本根结定位法是一个区分问题源头与末端, 据此确定干预优先级的决策框架。

  1. 识别标本: 在因果链中, 先发生的/根本原因是"本", 后发生的/继发症状是"标"。在空间上, 源头(四肢末端/根)是本, 末端(头面胸腹/结)是标。

  2. 缓急定序: 默认"治本"优先, 但有明确的例外——"中满"(急症/关键瓶颈)和"大小便不利"(功能受阻)必须先治标。急则治标, 缓则治本。

  3. 虚实影响排序: "病发而有余(实), 本而标之"——从本治起;"病发而不足(虚), 标而本之"——从标治起。虚证时系统承受力弱, 需要先缓解表面症状再追根溯源。

  4. 间甚并行: "间者并行, 甚者独行"——问题不太严重时可以标本同治, 问题严重时只能集中精力治一个。


A1 — 书中的应用 (Past Application)

案例 1: 先病后逆的治本原则

  • 问题: 先得病后出现气逆, 该治哪个?
  • 方法论的使用: "先病而后逆者治其本"——原发病是本, 气逆是标(继发), 治原发病则气逆自消。
  • 结论: 症状的出现顺序揭示了因果链, 先治因后治果。
  • 结果: 治本则标自消, 避免了在继发症状上浪费精力。

案例 2: 中满的紧急优先

  • 问题: 先得病后出现中满(腹部胀满), 按理应治本, 但中满很急, 怎么办?
  • 方法论的使用: "先病而后生中满者治其标"——虽然中满是标(继发), 但它阻塞了核心通道, 必须先解决。
  • 结论: 当标证(继发问题)威胁到系统核心功能时, 标的优先级临时提升。
  • 结果: 先解决紧急阻塞, 再回头治本。

A2 — 触发场景 (Future Trigger) ★

  1. 多问题纠缠: 面对一堆相互关联的问题, 不知道从哪个入手。
  2. 因果链追溯: 知道表现但不确定根因, 需要沿因果链回溯。
  3. 先治标还是先治本: 紧急问题(标)和根本问题(本)同时存在, 需要排序。

语言信号

  • "问题太多了, 不知道先解决哪个"
  • "根本原因到底是什么"
  • "紧急的和重要的怎么平衡"
  • "解决了A, B又冒出来了"

与相邻 skill 的区分

  • 与 excess-deficiency-decision 的区别: 虚实补泻解决"方向(补/泻)", 标本根结解决"顺序(先/后)"。两者独立但经常串联。
  • 与 timing-opportunity 的区别: 标本根结是"做什么的优先级", 时机选择是"何时做的时机窗口"。

E — 可执行步骤 (Execution)

  1. 列出所有问题并建立因果链

    • 列出所有问题, 标注相互之间的因果关系(A导致B, B导致C)。
    • 完成标准: 有明确的因果链图, 标注了时间先后顺序。
  2. 区分标本

    • 在因果链中: 先发生的/根本原因=本, 后发生的/继发表现=标。
    • 完成标准: 每个问题标注了"本"或"标", 并说明判断依据。
  3. 检查紧急例外

    • 是否存在"中满型"问题——虽然不是根因, 但阻塞了核心功能, 必须先解决?
    • 完成标准: 识别并标注紧急例外, 给出优先级调整理由。
  4. 确定执行顺序

    • 默认从本治起; 有紧急例外则先治标; 虚证时从标治起。
    • 完成标准: 给出明确的执行顺序和每步的理由。

B — 边界 (Boundary) ★

不要在以下情况使用

  • 问题孤立: 如果问题之间没有因果关系, 标本框架无法展开。
  • 教条治本: 不是所有情况都应该"先治本", 紧急情况必须先治标。

失败模式

  • 本标混淆: 把症状当原因, 在标上浪费精力而本持续恶化。
  • 教条主义: 无论多急都坚持"先治本", 忽视了紧急标证的威胁。

作者的盲点

  • 灵枢的标本主要关注时间先后和虚实, 现代问题还可能涉及资源约束、利益相关方优先级等额外维度, 需要扩展框架。

审计信息

  • 验证通过: V1 ✓ / V2 ✓ / V3 ✓
  • 测试通过率: {{%}} (详见 test-prompts.json)
  • 蒸馏时间: {{DATE}}

Frequently asked questions

What does the Root Cause Priority AI skill do?

用户面对多个相互关联的问题, 不知道先解决哪个时; 当需要区分根本原因 与表面症状时; 当问题有先后因果链需要追溯源头时。 不适用于: 只有一个简单问题的场景、问题之间没有因果关系的场景。

Why use Root Cause Priority on TypingMind?

Because you install it once and use it with any model. Root Cause Priority is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Root Cause Priority in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dhicoc/wuyun-liuqi-skills/tree/master/scripts/lib/neijing_snapshot/lingshu/root-cause-priority. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Root Cause Priority?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Root Cause Priority?

As many as you like. As long as a model supports skills, you can use Root Cause Priority with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Root Cause Priority AI skill free?

Yes. It is published on GitHub by dhicoc under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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