Negative Feedback

Community

dhicoc

negative-feedback

用户观察到某个力量/趋势/行为过度亢盛需要引入制衡时; 当系统出现"越用力越糟糕"的过冲现象时; 当需要设计自我调节机制防止系统走向极端时; 当用户说"物极必反"或"用力过猛反而坏事"时。不适用于: 需要持续单向推进不需要制衡的场景(如创业初期的全力冲刺); 问题本身就是力量不足而非亢盛的场景。

Overview

Publisher	dhicoc
Repository	`wuyun-liuqi-skills`
Skill name	`negative-feedback`
Stars	52
Forks	10
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 Negative Feedback AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/dhicoc/wuyun-liuqi-skills/tree/master/scripts/lib/neijing_snapshot/suwen/negative-feedback
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/dhicoc/wuyun-liuqi-skills/tree/master/scripts/lib/neijing_snapshot/suwen/negative-feedback

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/suwen/negative-feedback .claude/skills/negative-feedback

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Negative Feedback 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 Negative Feedback 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 Negative Feedback 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.

Negative Feedback — 亢害承制调控法

R — 原文 (Reading)

相火之下，水气承之；水位之下，土气承之；土位之下，风气承之；风位之下，金气承之；金位之下，火气承之；君火之下，阴精承之。帝曰：何也？岐伯曰：亢则害，承乃制，制则生化，外列盛衰，害则败乱，生化大病。

— 《黄帝内经·素问》，六微旨大论篇第六十八

I — 方法论骨架 (Interpretation)

任何力量如果不受制约地持续亢盛，最终会伤害系统本身——这就是"亢则害"。但自然界的健康系统中，每个亢盛的力量背后都跟着一个制约力量——这就是"承"。 "承乃制"——有了制约，系统才能保持动态平衡，维持正常的"生化"(运转发展)。如果制约机制缺失，系统就会走向"败乱"。

这个框架揭示了一个反直觉的道理：制约不是发展的阻碍，而是发展的前提。没有制约的亢盛不是"强大"，而是"正在走向崩溃的前兆"。

素问列举了六气之间的承制关系：火之下水承、水之下土承、土之下风承…… 每一对都是"亢盛力量→制约力量"的结构。这些承制关系是系统内置的负反馈环路——当A过度亢盛时， B就被激活来制约A，使系统回归平衡。

迁移到现代场景：严格的KPI(亢)需要配合创新指标(承)来制约；快速增长(亢)需要配合组织建设(承)来制约；强势领导(亢)需要配合 dissent 机制(承)来制约。关键是：承制机制要在亢盛之前就建好，而不是等亢盛出了问题再临时找。

A1 — 书中的应用 (Past Application)

案例 1: 六气的承制关系

问题: 为什么五运六气之中，每个主气之下都有一个"承"气？
方法论的使用: 素问逐一列出六气的承制配对：相火之下水气承之(水制火)，水位之下土气承之(土制水)，土位之下风气承之(木制土)……这不是随意搭配，而是按照五行相克的逻辑——每个力量都由"克它"的力量来制约。
结论: "亢则害承乃制制则生化"——有了承制，系统才能正常运转(生化)；失去承制，系统就会败乱。
结果: 理解承制关系的医生能判断"这个亢盛是正常的(有承制)还是危险的(失去承制)"，从而决定是否需要干预。

案例 2: 胜复循环的自动调节

问题: 当某个运气过度亢盛之后会发生什么？
方法论的使用: 至真要大论指出"有胜则复，无胜则否"——有过度亢盛(胜)就必定有反弹回复(复)，这是系统的自动调节机制。比如某年火气太盛(胜火)，随后就会有一股寒凉之气来回复平衡(复)。
结论: 胜复是自然的负反馈——过度的亢盛会自动唤起制约力量。但如果不等到自然回复就人为干预，或者更糟地继续推波助澜，就会破坏这个自动调节。
结果: 懂得胜复规律的医生在亢盛初起时不急于强力干预，而是顺势引导回复；不懂的医生可能在亢盛期继续助阳，加剧过冲。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

过冲现象: 系统中某个力量已经明显过度——指标飙高、行为极端、趋势过热——用户发现"越用力越糟糕"，需要引入制衡来纠偏。
设计自调节机制: 用户在构建一个新系统/组织/流程，需要提前内置制约机制，防止某个环节的亢盛失控。
单边推进后的反弹: 持续朝一个方向用力之后出现了反弹(团队倦怠、市场反噬、系统崩溃)，用户需要理解"为什么会这样"并设计承制。

语言信号 (用户的话里出现这些就应激活)

"越用力越糟糕"
"物极必反"
"用力过猛反而坏事"
"需要引入制衡/制约"
"这个趋势太猛了，会不会过热？"
"单方面推太远了，需要拉回来"
"系统缺乏自我调节机制"

与相邻 skill 的区分

与 zheng-xie-assessment 的区别: 亢害承制是发现"亢盛→引入制约"的调控动作，正邪虚实是判断"虚(不足)还是实(过盛)"的诊断动作。前者是"做了什么"，后者是"判断是什么"。两者经常串联使用：先用正邪虚实判断出"实(亢盛)"，再用亢害承制来"引入承制"。
与 cascade-prediction 的区别: 传变预测是"问题沿链条传播到下游"，亢害承制是"亢盛力量唤起制约力量"。前者是单向传播，后者是双向对抗。

E — 可执行步骤 (Execution)

当 skill 被激活后, agent 应按以下步骤执行:

识别哪个力量正在亢盛
- 观察系统中哪个指标、行为、趋势、力量正在持续走高、过度膨胀、失去节制。
- 判断亢盛的程度：是"正常范围内的旺盛"还是"已经超出平衡的亢盛"？
- 完成标准: 明确标注"亢盛力量是什么"以及"亢盛的具体表现"。
找到或引入对应的制约力量(承)
- 按照"克它"的逻辑找到天然制约者：增长过快→质量/合规来承，强势领导→ dissent 机制来承，高产出→可持续发展来承。
- 如果天然制约者已存在但力量不足，分析为什么不足以制衡(是被压制了还是太弱了)。
- 如果不存在天然的制约力量，需要人为引入一个。
- 完成标准: 明确标注"承制力量是什么"以及它应该如何制约亢盛力量。
建立制衡机制使系统回归平衡
- 设计具体的承制机制：可能是制度(审批流程)、指标(对冲KPI)、文化(鼓励反对意见)、技术(熔断机制)等。
- 确保承制力量不会矫枉过正——制衡的目标是"制则生化"(回归平衡)，不是"彻底压制"。
- 完成标准: 产出制衡方案，包括：承制机制是什么、何时触发、何时退出、如何避免矫枉过正。

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

需要持续单向推进的阶段: 创业初期、攻坚阶段、危机应对——这些场景需要的是全力推进，过早引入制衡会束缚行动力。制衡是稳态管理的工具，不是冲锋阶段的工具。
问题本身就是力量不足: 如果系统的问题是"太弱"而不是"太亢"，需要的是补强(参见 zheng-xie-assessment 的"虚则补")，而不是引入更多制约。

作者在书中警告的失败模式

不知承制而助亢——看到亢盛就以为是"强"而继续推波助澜，这是"亢则害"的直接原因。素问明确警告：亢盛而不制约，结局是"害则败乱，生化大病"。
承制过度——制约力量本身也可能亢盛，导致系统从"亢盛"跳到"压抑"，两个极端都不好。"制"的目标是"生化"而非"消灭"。

作者的盲点 / 时代局限

素问的承制关系是固定的(五行相克配对)，现实中的制约关系往往更复杂、更多对多。需要灵活寻找而非套用固定模式。
古代关注的是自然界的亢害承制(气候、运气)，现代场景中的"亢盛"可能更隐蔽(如隐性文化压力、算法的正反馈环路)，识别难度更高。

容易混淆的邻近方法论

"负反馈"——这是亢害承制的现代科学表述，但素问版本更强调"为什么要承"（亢则害）和"承的目标"（制则生化），不仅描述机制还给出价值判断。
"三权分立"——政治学中的权力制衡是亢害承制在制度设计上的体现，但素问的框架更通用，可用于任何系统(不仅是政治)。

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: 2026-04-18

Frequently asked questions

What does the Negative Feedback AI skill do?

Why use Negative Feedback on TypingMind?

Because you install it once and use it with any model. Negative Feedback 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 Negative Feedback 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/suwen/negative-feedback. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Negative Feedback?

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 Negative Feedback?

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

Is the Negative Feedback 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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Negative Feedback

Overview