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Bottleneck Unblock

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dhicoc
bottleneck-unblock

用户面对系统阻塞/瓶颈问题, 需要找到阻塞点并疏通时; 当系统"上实下虚" 或"上虚下实"等方向性阻塞时; 当直接在问题点干预无效, 需要另辟蹊径时。 不适用于: 没有阻塞的问题、可以简单修复的场景、纯资源不足(非阻塞型)的场景。

Overview

Publisherdhicoc
Repositorywuyun-liuqi-skills
Skill namebottleneck-unblock
Stars
52
Forks
10
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepository
  • 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 Bottleneck Unblock 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/bottleneck-unblock
  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/bottleneck-unblock .claude/skills/bottleneck-unblock
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bottleneck Unblock 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 Bottleneck Unblock 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 Bottleneck Unblock 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.

解结通滞法

R — 原文 (Reading)

一经上实下虚而不通者, 此必有横络盛加于大经, 令之不通。 视而泻之, 此所谓解结也。 上寒下热, 推而上之; 上热下寒, 引而下之; 大热遍身, 推而散之。 夫善用针者, 取其疾也, 犹拔刺也, 犹雪污也, 犹解结也, 犹决闭也。

— 黄帝/岐伯, 刺节真邪第七十五、九针十二原第一

I — 方法论骨架 (Interpretation)

解结通滞法是一个识别系统阻塞点并精准疏通的问题解决框架。

  1. 找到"横络": 阻塞的真正原因: 系统不通往往不是整条链路都有问题, 而是"横络盛加于大经"——某个交叉点的压迫/阻塞导致了全线不通。找到这个点, 问题迎刃而解。

  2. 诊断方法: 切而循之: "用针者, 必先察其经络之实虚, 切而循之, 按而弹之, 视其应动者乃后取之"——通过沿线路逐一排查, 找到响应异常的点。

  3. 方向性疏通: 阻塞有不同的方向模式——上寒下热(推而上之)、上热下寒(引而下之)、大热遍身(推而散之)。疏通不是无方向的, 必须判断阻塞的方向性。

  4. 四喻定位: 拔刺(精准取出)、雪污(清除污染)、解结(打开死结)、决闭(疏通堵塞)——不同性质的阻塞用不同的疏通方式。

A1 — 书中的应用 (Past Application)

案例 1: 一经上实下虚的解结

  • 问题: 一条经脉上部充实下部空虚, 气血不通, 是什么原因?
  • 方法论的使用: 不是经脉本身的问题, 而是"横络盛加于大经"——有一条横向的络脉压迫了主通道。解法: "视而泻之"——找到压迫点, 在那里泻除多余的压迫。
  • 结论: 阻塞往往来自意料之外的第三方因素(横络), 而非主通道本身的问题。
  • 结果: 在压迫点精准疏通后, 主通道自然恢复通畅。

案例 2: 上寒下热的推而上之

  • 问题: 上半身寒下半身热, 如何处理?
  • 方法论的使用: "先刺其项太阳, 久留之, 已刺则熨项与肩胛, 令热下合乃止, 此所谓推而上之者也"——在颈部(上方的控制点)干预, 将热量推向上部。
  • 结论: 不是在寒的地方加热, 而是在控制点(颈部)操作, 通过调节"阀门"来分配资源。
  • 结果: 通过控制点调节, 实现上下温度重新平衡。

A2 — 触发场景 (Future Trigger) ★

  1. 流程阻塞: 工作流程/信息流/决策链中某个环节堵塞, 导致上下游失衡。
  2. 资源错配: 系统一端资源过剩另一端不足, 但不是总量问题而是流通问题。
  3. 久拖不决: 问题长期存在, 局部修复无效, 可能是某个隐藏的瓶颈。

语言信号

  • "到处卡住了"
  • "上面太多了下面不够"
  • "某个环节堵住了整个流程"
  • "直接修不好, 需要另想办法"

E — 可执行步骤 (Execution)

  1. 识别阻塞模式

    • 判断是全系统阻塞(全线不通)还是方向性阻塞(一端实一端虚)。如果是方向性的, 确定是"上实下虚""上虚下实"还是"全面淤滞"。
    • 完成标准: 明确标注阻塞模式。

  2. 排查阻塞点

    • "切而循之"——沿流通路径逐一排查, 找到响应异常的点(横络)。
    • 完成标准: 定位到具体的阻塞点, 并说明为什么是它。

  3. 选择疏通方向

    • 上寒下热→推而上之(将资源向上推); 上热下寒→引而下之(将资源向下引); 全面淤滞→推而散之(全面疏散)。
    • 完成标准: 给出疏通方向和具体动作。

  4. 验证疏通效果

    • 疏通后应有可感知的变化(如"热下合乃止")。如果没有变化, 可能定位错误, 需要重新排查。
    • 完成标准: 设定验证指标。

B — 边界 (Boundary) ★

不要在以下情况使用

  • 资源绝对不足: 如果问题不是阻塞而是总量不够(如预算不足), 疏通无法解决——需要增加资源而非疏通。
  • 结构已毁: "脉血结于中中有着血, 血寒故宜灸之"——有些阻塞已经造成结构性损伤, 单纯疏通不够, 需要修复。

失败模式

  • 定位错误: 在错误的位置疏通, 不仅无效还可能制造新的阻塞。
  • 过度疏通: 疏通后继续操作, 导致系统从"阻塞"变为"泄漏"。

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 Bottleneck Unblock AI skill do?

用户面对系统阻塞/瓶颈问题, 需要找到阻塞点并疏通时; 当系统"上实下虚" 或"上虚下实"等方向性阻塞时; 当直接在问题点干预无效, 需要另辟蹊径时。 不适用于: 没有阻塞的问题、可以简单修复的场景、纯资源不足(非阻塞型)的场景。

Why use Bottleneck Unblock on TypingMind?

Because you install it once and use it with any model. Bottleneck Unblock 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 Bottleneck Unblock 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/bottleneck-unblock. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bottleneck Unblock?

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 Bottleneck Unblock?

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

Is the Bottleneck Unblock 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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