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Zhanlue Zhanshu Bianzheng

Community
kangarooking
zhanlue-zhanshu-bianzheng

当用户处于整体被动但需要在局部制造主动时激活此skill。 典型触发信号:公司整体在收缩但士气低落、资源劣势下不知如何破局、宏观被动中需要找到微观突破口。 不调用场景:双方实力相当正常竞争、已有整体优势只需执行、问题不在攻守转换层面。 与"十六字诀"skill的区别:本skill解决"宏观被动中如何制造微观主动"(攻守辩证),后者解决"根据对手状态选择节奏"(时机判断)。

Overview

Publisherkangarooking
Repositorymao-selected-works-skill
Skill namezhanlue-zhanshu-bianzheng
Stars
123
Forks
16
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Zhanlue Zhanshu Bianzheng 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/kangarooking/mao-selected-works-skill/tree/main/zhanlue-zhanshu-bianzheng
  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/kangarooking/mao-selected-works-skill.git /tmp/mao-selected-works-skill
mkdir -p .claude/skills
cp -r /tmp/mao-selected-works-skill/zhanlue-zhanshu-bianzheng .claude/skills/zhanlue-zhanshu-bianzheng
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Zhanlue Zhanshu Bianzheng 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 Zhanlue Zhanshu Bianzheng 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 Zhanlue Zhanshu Bianzheng 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.

R — 原文 (Reading)

"在第一和第二阶段即敌之进攻和保守阶段中,应该是战略防御中的战役和战斗的进攻战,战略持久中的战役和战斗的速决战,战略内线中的战役和战斗的外线作战。" — 《论持久战》(1938年5月)

"为了进攻而防御,为了前进而后退,为了向正面而向侧面,为了走直路而走弯路,是许多事物在发展过程中所不可避免的现象,何况军事运动。" — 《中国革命战争的战略问题》(1936年12月)

I — 方法论骨架 (Interpretation)

  1. 战略和战术可以在同一时间方向相反——你可以在战略上防守的同时在战术上进攻,这是有意设计的战略张力,不是自相矛盾。
  2. 防御中的进攻:公司整体在收缩不代表每个战场都要退缩。选一个最有把握的点(某个细分客户群或某个产品功能),集中资源快速打赢一场"速决战",用小胜利提振士气、积累信心。
  3. 持久中的速决:长期竞争(持久战)不等于每场仗都慢慢打。恰恰相反,每场具体的战役都要追求速战速决——快速投入、快速打赢、快速收获,然后在下一个点重复。
  4. 内线中的外线:被包围不等于被动挨打。在对手的包围圈中寻找缝隙,从内向外打出局部反击——对手包围你的同时,你也可以在局部包围对手。
  5. 核心洞见是"攻守在不同层级可以同时存在且方向相反"——整体被动中制造局部主动,通过无数个局部的主动来逐步改变整体力量对比。
  6. 这不是"随机应变"的灵活,而是有意设计的战略张力——退是为了进,守是为了攻,弯路是为了直路。

A1 — 书中应用 (Past Application)

应用1:集中兵力的实战应用 — 第一次反"围剿" (c07)

  • 问题:国民党以优势兵力围剿红军,红军整体处于战略防御。
  • 方法使用:在整体防御中,不处处防守,而是选择最有利的战机和战场,集中兵力打进攻战——等了25天找到张辉瓒部,一战歼灭。整体退却中的局部进攻。
  • 结论:两次想打谭道源但条件不好就忍住撤回(防御中的耐心),等到好时机就果断集中兵力歼灭(防御中的进攻)。"宁可退让,持重待机"。
  • 结果:前四次反"围剿"均用此辩证法取得胜利。整体处于劣势但每次具体战役都形成局部优势。

应用2:诱敌深入 — "将欲取之必先与之" (c08)

  • 问题:面对强敌进攻,"御敌于国门之外"(处处防守)还是主动退却?
  • 方法使用:毛泽东选择主动退却(战略防御/后退),把敌人引入根据地内部,拉长其补给线,消耗其力量,然后集中兵力反击(战役进攻)。"只有丧失才能不丧失"。
  • 结论:第五次反"围剿"拒绝此辩证法(不愿丧失一寸土地),结果丧失了全部根据地。
  • 结果:正反两面对比极具说服力——前四次用辩证法胜利,第五次不用则惨败。

A2 — 触发场景 (Future Trigger)

  1. 整体收缩但士气低迷:公司被迫缩减战线、裁员、砍项目,团队士气低落。用户会说:"大家都很消极""感觉在走下坡路""团队没有斗志"。
  2. 被巨头挤压,全面被动:每个战场都在输,每个产品线都被对手压制。用户会说:"到处都在丢客户""对方全面碾压我们"。
  3. 资源劣势下的决策焦虑:资源有限,既怕不反击就等死,又怕反击了输更多。用户会说:"该不该硬拼一下""不反击就等死,反击怕死更快"。
  4. 长期竞争中的疲惫感:持久战打久了,团队疲惫,看不到希望。用户会说:"看不到尽头""不知道什么时候才能翻盘"。

语言信号:用户提到"被动""全面挨打""士气低落""看不到希望""该不该反击""收缩但心有不甘""感觉被围"等词汇时,应优先激活此skill。

与相邻skill区分:

  • vs 十六字诀灵活策略:本skill = "宏观被动中制造微观主动的原理",后者 = "根据对手状态选择具体行动"
  • vs 不对称战略:本skill = "攻守层级的辩证关系",后者 = "弱者重新定义竞争范式"
  • vs 集中优势兵力:本skill = "为什么要集中(辩证原理)",后者 = "怎么集中(操作方法)"

E — 可执行步骤 (Execution)

步骤1:承认宏观被动,锁定微观突破口

  • 诚实地承认当前整体处于战略防御(不要自欺欺人说"我们其实还行")。
  • 在所有战场中找出最有把握打赢的那一个点——可能是某个对手最薄弱的细分客户群、某个你最擅长的产品功能、或某个对手忽视的区域。
  • 完成标准:明确写出"我们在整体___方面处于被动,但在___这个具体点上,我们有___的优势,可以打赢一场局部战役"。

步骤2:打一场"防御中的进攻战"

  • 在选定的突破口集中资源(人力、预算、时间),追求速战速决——快速出结果,不要拖成消耗战。
  • 这场小战役的目标不是改变大局,而是:(1)提振团队士气;(2)验证战法是否有效;(3)积累一个小胜利的案例。
  • 判停点:如果找不到任何有把握的突破口,说明问题可能在基本面上——回到不对称战略或根据地建设,先构建能力。

步骤3:用局部胜利积累整体优势

  • 每次局部胜利后,不要急于扩大战线(那会从进攻变为冒进),而是巩固胜利成果,选下一个突破口。
  • 追踪局部胜利对整体力量对比的影响:客户口碑是否在扩散?团队信心是否在恢复?对手是否开始调整部署?
  • 完成标准:建立"局部胜利日志",记录每次微观进攻的结果(赢了什么、学到了什么、对全局的影响是什么),每季度回顾整体力量对比是否在改变。

B — 边界 (Boundary)

不要使用的场景

  1. 已有整体优势时:如果你已经在整体上占优,应该乘胜追击全面进攻,不需要"防御中的进攻"——直接用集中优势兵力打歼灭战。
  2. 紧急危机时:公司面临生死存亡(现金流即将断裂),此时不需要辩证法,需要的是紧急求生——先活下来再说。
  3. 团队尚未形成基本战斗力时:如果连一场小仗都打不赢(产品不行、团队不行),先解决基本功问题,不要幻想"防御中进攻"。

失败模式(来自反例)

  • 速胜论(ce05):把"防御中的进攻"理解为全面反攻——一个小胜利后就急于"一举拿下"。毛泽东警告:"急性病的速胜论者熬不过持久战的艰难路程,一到形势稍为好转,就吹起了战略决战的声浪"。
  • 逃跑主义(ce16):从冒进极端跳到逃跑极端——一遇到挫折就全面放弃。"左"倾路线的第一阶段是冒险主义,第二阶段保守主义,最后变成逃跑主义。防御不是逃跑。
  • 消极防御(ce11):"御敌于国门之外",试图守住每一个阵地,结果每个阵地都守不住。"不愿意丧失一部分土地,结果丧失了全部土地"。

作者盲点

  • 毛泽东对"防御中进攻"的论述主要在军事领域,对"什么规模的进攻才算战术级别"缺乏精确界定。商业启示:需要根据公司体量定义"局部战役"的边界——对10人公司,拿下1个大客户就是一场战略级进攻;对千人公司,需要更大规模的战役才算"战术"。

相关 skills

  • 十六字诀灵活策略 (composes-with): 战略-战术辩证法提供"宏观被动中制造微观主动"的原理,十六字诀提供具体的节奏执行步骤(退→扰→打→追)。
  • 不对称战略 (composes-with): 不对称战略定义弱者的竞争范式,战略-战术辩证法处理该范式内每个阶段"防守中如何进攻"的具体操作。
  • 三阶段持久战模型 (composes-with): 持久战规划宏观的三阶段时间线,战略-战术辩证法处理每个阶段内"防守中进攻"的微观操作。宏观节奏与微观战术的配合。
  • 集中优势兵力歼灭战 (composes-with): 战略-战术辩证法解释"为什么要集中兵力打局部进攻"的辩证原理,集中优势兵力提供"怎么集中"的具体操作方法。
  • 战略藐视战术重视 (composes-with): 战略-战术辩证法是策略层的设计(攻守层级的辩证),战略藐视战术重视是心态层的管理(信心与谨慎的平衡)。策略需要正确的心态来支撑执行。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Zhanlue Zhanshu Bianzheng AI skill do?

当用户处于整体被动但需要在局部制造主动时激活此skill。 典型触发信号:公司整体在收缩但士气低落、资源劣势下不知如何破局、宏观被动中需要找到微观突破口。 不调用场景:双方实力相当正常竞争、已有整体优势只需执行、问题不在攻守转换层面。 与"十六字诀"skill的区别:本skill解决"宏观被动中如何制造微观主动"(攻守辩证),后者解决"根据对手状态选择节奏"(时机判断)。

Why use Zhanlue Zhanshu Bianzheng on TypingMind?

Because you install it once and use it with any model. Zhanlue Zhanshu Bianzheng 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 Zhanlue Zhanshu Bianzheng in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kangarooking/mao-selected-works-skill/tree/main/zhanlue-zhanshu-bianzheng. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Zhanlue Zhanshu Bianzheng?

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 Zhanlue Zhanshu Bianzheng?

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

Is the Zhanlue Zhanshu Bianzheng AI skill free?

Yes. It is published on GitHub by kangarooking 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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