Agent skill

Maodun Techuxing

by kangarooking in kangarooking/mao-selected-works-skill

当用户准备套用一个成功方法论(别人的或自己过去的)到新场景时激活此skill。典型触发信号: "某公司用了X方法成功了,我们也该试试""我之前这么做有效,继续做""行业最佳实践是Y"。

MITAuto-check passed

Install Maodun Techuxing

skills CLI
$ npx skills add kangarooking/mao-selected-works-skill --skill maodun-techuxing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install kangarooking/mao-selected-works-skill maodun-techuxing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/kangarooking/mao-selected-works-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/maodun-techuxing .claude/skills/maodun-techuxing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
maodun-techuxing
GitHub stars
114
Token cost
~811 tokens
SKILL.md length
97 words
Files
2
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

当用户准备套用一个成功方法论(别人的或自己过去的)到新场景时激活此skill。典型触发信号: "某公司用了X方法成功了,我们也该试试""我之前这么做有效,继续做""行业最佳实践是Y"。

  • Works in 5 steps: 世界上没有万能方法论。不同性质的问题需要不同性质的解决方案,这是铁律。 → 判断问题的"质"(性质)是关键一步。表面相似的问题可能性质完全不同——员工离职可能… → 建立"一般-特殊-更加特殊"的三层认知路径:先理解一般规律(行业趋势),再把握特殊… → …
  • SKILL.md covers R — 原文 (Reading), I — 方法论骨架 (Interpretation), A1 — 书中应用 (Past Application) and A2 — 触发场景 (Future Trigger), plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Maodun Techuxing is an agent skill from kangarooking/mao-selected-works-skill. 当用户准备套用一个成功方法论(别人的或自己过去的)到新场景时激活此skill。典型触发信号: "某公司用了X方法成功了,我们也该试试""我之前这么做有效,继续做""行业最佳实践是Y"。 不调用场景:用户面对的是同一类问题的重复出现、需要的是执行力而非方法论选择。 与"矛盾分析法"的区别:本skill强调"每个问题性质不同需不同方法",后者强调"找到最重要的那个问题"。

Its SKILL.md is about 810 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `test-prompts.json`).

The repository describes itself as: An AI skill pack distilling Selected Works of Mao Zedong into reusable cognition, strategy, organization, and execution modules. The licence is MIT.

Example prompts

  • “某公司用了X方法成功了,我们也该试试”
  • “我之前这么做有效,继续做”
  • “行业最佳实践是Y”
  • “/maodun-techuxing”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. 世界上没有万能方法论。不同性质的问题需要不同性质的解决方案,这是铁律。
  2. 判断问题的"质"(性质)是关键一步。表面相似的问题可能性质完全不同——员工离职可能是因为薪酬、管理、成长空间中的任何一个,不能一刀切。
  3. 建立"一般-特殊-更加特殊"的三层认知路径:先理解一般规律(行业趋势),再把握特殊规律(公司阶段),最后深入到更加特殊的规律(具体情境)。
  4. 照搬别人成功方法(教条主义)是最常见也最危险的陷阱。别人成功的前提条件你可能不具备。
  5. 照搬自己过去的成功经验同样危险——环境变了,方法的适用条件也变了。

What it can do on your machine

Read from SKILL.md and the folder at commit 5058fe4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Maodun Techuxing loads about 811 tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 97 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~811

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from kangarooking/mao-selected-works-skill at commit 5058fe4, republished under its MIT licence (© kangarooking). 97 words, ~811 tokens.

Download SKILL.mdSave it as .claude/skills/maodun-techuxing/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
maodun-techuxing
description
当用户准备套用一个成功方法论(别人的或自己过去的)到新场景时激活此skill。典型触发信号: "某公司用了X方法成功了,我们也该试试""我之前这么做有效,继续做""行业最佳实践是Y"。 不调用场景:用户面对的是同一类问题的重复出现、需要的是执行力而非方法论选择。 与"矛盾分析法"的区别:本skill强调"每个问题性质不同需不同方法",后者强调"找到最重要的那个问题"。
source_book
《毛泽东选集第1-5卷》 毛泽东
source_chapter
矛盾论(1937); 中国革命战争的战略问题(1936); 抗日游击战争的战略问题(1938)
tags
具体问题具体分析, 反教条主义, 方法论适配, 情境判断, 分类思维

R — 原文 (Reading)

"不同质的矛盾,只有用不同质的方法才能解决。例如,无产阶级和资产阶级的矛盾,用社会主义革命的方法去解决;人民大众和封建制度的矛盾,用民主革命的方法去解决……用不同的方法去解决不同的矛盾,这是马克思列宁主义者必须严格地遵守的一个原则。" — 《矛盾论》(1937年8月)

I — 方法论骨架 (Interpretation)

  1. 世界上没有万能方法论。不同性质的问题需要不同性质的解决方案,这是铁律。
  2. 判断问题的"质"(性质)是关键一步。表面相似的问题可能性质完全不同——员工离职可能是因为薪酬、管理、成长空间中的任何一个,不能一刀切。
  3. 建立"一般-特殊-更加特殊"的三层认知路径:先理解一般规律(行业趋势),再把握特殊规律(公司阶段),最后深入到更加特殊的规律(具体情境)。
  4. 照搬别人成功方法(教条主义)是最常见也最危险的陷阱。别人成功的前提条件你可能不具备。
  5. 照搬自己过去的成功经验同样危险——环境变了,方法的适用条件也变了。

A1 — 书中应用 (Past Application)

应用1:中国革命战争的战略问题 — 三层认知路径
  • 问题:党内有人照搬苏联内战经验或北伐战争经验指导中国革命战争,屡遭失败。
  • 方法使用:毛泽东建立三层认知:战争一般规律(战争的共性)-> 革命战争特殊规律(革命战争的个性)-> 中国革命战争更加特殊的规律(中国条件的独特性)。每一层都不可跳过。
  • 结论:中国革命战争有其特殊的规律——敌强我弱、农村包围城市——不能照搬苏联城市起义模式。
  • 结果:基于这一分析确立的战略路线,最终取得全国胜利;照搬苏联经验的教条主义路线导致1931-1934年革命力量损失90%。
应用2:矛盾论 — 反对教条主义和经验主义
  • 问题:党内教条主义者把马列主义当公式套用,经验主义者拒绝理论提升。
  • 方法使用:毛泽东用苏联内战和中国革命战争的对比说明:同样的原则在不同的具体条件下必须有不同的应用方式。
  • 结论:"矛盾的普遍性即寓于矛盾的特殊性之中"——一般原理必须通过具体分析才能落地。
  • 结果:矛盾论成为纠正教条主义和经验主义的哲学武器。

A2 — 触发场景 (Future Trigger)

  1. 照搬最佳实践:团队想套用某个知名公司的方法论(OKR、敏捷、增长黑客等),但没分析自己条件的特殊性。用户会说:"Google/字节/阿里就是这么做的,我们也该这样做"。
  2. 过去经验失灵:上次有效的方法这次不灵了,团队困惑。用户会说:"我们之前这样做成功的啊,怎么现在不行了""行业变了但方法没变"。
  3. 一刀切决策:对所有客户/市场/团队用同一套方法,效果参差不齐。用户会说:"为什么这个方法对A团队有效对B团队无效"。
  4. 方法论选择困难:面临多种管理/产品/营销方法论不知该选哪个。用户会说:"有这么多种方法,该用哪个""哪个方法适合我们"。
  5. 顾问/专家推销万能方案:外部顾问或行业专家推荐"放之四海而皆准"的解决方案。用户会说:"专家说我们应该这样做"。

语言信号:用户提到"最佳实践""行业标杆""别人也是这么做的""标准做法""通用方案"等词汇时,应激活此skill进行性质分析。

与相邻skill区分:

  • vs 矛盾分析法:本skill关注"用什么方法解决",后者关注"哪个问题最重要"
  • vs 实事求是信息加工法:本skill是方法论选择框架,后者是信息处理框架
  • vs 实践认识论:本skill在行动前做性质判断,后者在行动后做认知提升

E — 可执行步骤 (Execution)

步骤1:问题性质分析
  • 对当前问题做三层追问:(1) 这个问题属于哪一类一般问题?(2) 在我们公司/团队的特殊条件下有什么不同?(3) 在当前这个具体情境中有什么更加特殊的因素?
  • 完成标准:能明确说出"我们的问题看起来像X类问题,但因为我们具备___条件,所以它的性质更接近Y"。
步骤2:前提条件对照
  • 拿出准备使用的方法论,列出它的隐含前提条件(这个方法论在什么条件下有效?)。逐一对照:我们的情况是否满足这些前提?
  • 判停点:如果关键前提条件不满足,立即停止套用,转至步骤3。
步骤3:适配改造
  • 根据步骤1的性质分析和步骤2的前提对照,对方法论做适配改造:保留核心原理,调整具体做法以匹配自身条件。
  • 完成标准:产出一份"适配说明"——"原方法要求___,我们的条件是___,因此我们调整为___。调整的理由是___。"

B — 边界 (Boundary)

不要使用的场景
  1. 真正的通用问题时:有些问题确实是通用问题(如基础代码规范、财务合规),不需要特殊方法论,直接用通用方案即可。
  2. 时间极度紧迫时:如果必须立刻行动,先按通用方案执行,事后复盘时再做特殊性分析。
  3. 已经验证过的重复场景:如果是同一类问题的第N次处理,且之前的方法已被验证有效,不需要每次都重新分析。
失败模式(来自反例)
  • 教条主义(ce01):拥有"理论武装"后反而更固执——把方法论当信仰而非工具,面对与理论不符的现实首先怀疑现实而非理论。
  • "正规化"陷阱(ce22):为了追求"看起来专业"而抛弃经过验证的有效做法。创业阶段用游击战法打赢了,规模扩大后为了"正规"而全盘抛弃,代之以看似专业实则无效的大公司做法。
  • 形式主义(ce15):非黑即白地评价方法论——要么全盘接受要么全盘否定,拒绝承认每个方法论都有其适用范围和局限性。
作者盲点
  • 毛泽东强调"具体情况具体分析"的同时,在某些时期自己也犯了教条主义的错误(如大跃进时期套用群众运动的方法解决经济问题)。教训:反教条主义本身也不能教条化——有时候简单问题的简单解法就是最优解。

相关 skills

  • 矛盾分析法 (depends-on): 矛盾特殊性原则是矛盾分析法的延伸——先用矛盾分析法找到主要矛盾,再用特殊性原则分析该矛盾的独特性质,选择适配的解决方法。
  • 实践认识论 (composes-with): 特殊性分析需要实践验证——判断问题性质后,必须回到实践中检验方法是否适配,两者构成"性质判断→实践验证"的闭环。

© kangarooking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in maodun-techuxing of kangarooking/mao-selected-works-skill.

  • SKILL.md
  • test-prompts.json

Open the folder on GitHubat commit 5058fe4

Compare with similar skills

Maodun Techuxing next to the 2 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Maodun Techuxing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Maodun Techuxing this skillkangarooking/mao-selected-works-skill114—~811Automated safety check: PassMIT
Maodun Fenxikangarooking/mao-selected-works-skill114—~914Automated safety check: PassMIT
Jianmiezhan Jizhong Binglikangarooking/mao-selected-works-skill114—~1.1kAutomated safety check: PassMIT

Similar skills

  • Maodun Fenxi

    kangarooking/mao-selected-works-skill

    当用户面对多个相互交织的问题、无法判断优先级、陷入"什么都重要"的决策瘫痪时激活此skill. An agent skill from kangarooking/mao-selected-works-skill.

    114 GitHub stars~914 tokensUpdated 5 mo ago
    Auto-check passed
  • Jianmiezhan Jizhong Bingli

    kangarooking/mao-selected-works-skill

    当用户资源有限但面临多个机会/威胁,需要在多个方向间做取舍时激活。典型触发信号: "5个客户机会同时出现""要不要同时做ToB和ToC""资源不够分怎么办"。

    114 GitHub stars~1.1k tokensUpdated 5 mo ago
    Auto-check passed

More from kangarooking/mao-selected-works-skill

All 13 skills in this repo
  • Buduicheng Zhanlue

    kangarooking/mao-selected-works-skill

    当用户作为弱势方面对强势竞争者、感觉"处处被动无法招架"时激活此skill. An agent skill from kangarooking/mao-selected-works-skill.

    114 GitHub stars~892 tokensUpdated 5 mo ago
    Auto-check passed
  • Chijiuzhan San Jieduan

    kangarooking/mao-selected-works-skill

    当用户面对明显强于自己的对手(巨头入场、资源差距、品牌劣势)需要规划长期竞争策略时激活. An agent skill from kangarooking/mao-selected-works-skill.

    114 GitHub stars~1k tokensUpdated 5 mo ago
    Auto-check passed
  • Diaocha Yanjiu

    kangarooking/mao-selected-works-skill

    当用户即将基于二手信息(报告、传闻、他人的总结)做重大决策,或团队出现了"坐在办公室拍脑袋"的倾向时激活. An agent skill from kangarooking/mao-selected-works-skill.

    114 GitHub stars~905 tokensUpdated 5 mo ago
    Auto-check passed
  • Shijian Renshilun

    kangarooking/mao-selected-works-skill

    当用户陷入"分析瘫痪"(想做但不敢行动)或"盲目行动"(做了但不总结不提升)时激活此skill. An agent skill from kangarooking/mao-selected-works-skill.

    114 GitHub stars~961 tokensUpdated 5 mo ago
    Auto-check passed
  • Shiliuzijue

    kangarooking/mao-selected-works-skill

    当用户需要根据竞争对手的状态选择自己的行动节奏时激活此skill. An agent skill from kangarooking/mao-selected-works-skill.

    114 GitHub stars~951 tokensUpdated 5 mo ago
    Auto-check passed
  • Shishiqiushi Sigao

    kangarooking/mao-selected-works-skill

    当用户面对大量杂乱信息(用户反馈、竞品数据、市场报告、内部指标)需要从中提取决策信号时激活. An agent skill from kangarooking/mao-selected-works-skill.

    114 GitHub stars~899 tokensUpdated 5 mo ago
    Auto-check passed

Questions about Maodun Techuxing

What does Maodun Techuxing do?

当用户准备套用一个成功方法论(别人的或自己过去的)到新场景时激活此skill。典型触发信号: "某公司用了X方法成功了,我们也该试试""我之前这么做有效,继续做""行业最佳实践是Y"。. Maodun Techuxing is an agent skill from kangarooking/mao-selected-works-skill.

How do I install Maodun Techuxing in Claude Code?

Run `npx skills add kangarooking/mao-selected-works-skill --skill maodun-techuxing -a claude-code`. Or copy the skill folder (maodun-techuxing in kangarooking/mao-selected-works-skill) into .claude/skills/maodun-techuxing in your project. Claude Code loads it when a task matches its description.

How do I install Maodun Techuxing in Codex?

Run `npx skills add kangarooking/mao-selected-works-skill --skill maodun-techuxing -a codex`. Or copy the skill folder (maodun-techuxing in kangarooking/mao-selected-works-skill) into .agents/skills/maodun-techuxing in your project. Codex loads it when a task matches its description.

Can I use Maodun Techuxing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add kangarooking/mao-selected-works-skill --skill maodun-techuxing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/maodun-techuxing, .gemini/skills/maodun-techuxing, .github/skills/maodun-techuxing and .opencode/skills/maodun-techuxing in your project.

What does Maodun Techuxing need to run?

SKILL.md names no scripts, command-line tools or credentials: Maodun Techuxing is instructions for the agent only.

Does Maodun Techuxing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Maodun Techuxing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Maodun Techuxing use?

Maodun Techuxing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Maodun Techuxing use?

About 811 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Maodun Techuxing?

Skills that share tags, products or a category with Maodun Techuxing: Maodun Fenxi (kangarooking/mao-selected-works-skill, 114 stars) and Jianmiezhan Jizhong Bingli (kangarooking/mao-selected-works-skill, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Maodun Techuxing?

kangarooking (a GitHub user) maintains it in kangarooking/mao-selected-works-skill, which has 114 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on May 2, 2026.

Source: kangarooking/mao-selected-works-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.