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Agent Skill · 研究检索

munger-worldly-wisdom(芒格世俗智慧)

munger-worldly-wisdom 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

munger-worldly-wisdom 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 37,100。

总安装 1,797周安装 72GitHub Stars 98下载 582核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:munger-worldly-wisdom(芒格世俗智慧)
来源仓库:https://github.com/erichowens/some_claude_skills
仓库路径:skills/munger-worldly-wisdom
安装命令:
npx skills add https://github.com/erichowens/some_claude_skills --skill munger-worldly-wisdom
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/erichowens/some_claude_skills --skill munger-worldly-wisdom

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,汇集世俗智慧类内容。适合在人生规划、学习策略或问题解决中获取启发。可整理名言、案例或方法论,但需结合具体情境判断适用性。

安装命令:npx skills add https://github.com/erichowens/some_claude_skills --skill munger-worldly-wisdom。注意区分普遍原则与个别经验,避免教条化应用。

来源仓库内路径:skills/munger-worldly-wisdom

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/erichowens/some_claude_skills --skill munger-w…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

munger-worldly-wisdom 怎么安装?

在终端执行 npx skills add https://github.com/erichowens/some_claude_skills --skill munger-worldly-wis…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

munger-worldly-wisdom 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

munger-worldly-wisdom 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

munger-worldly-wisdom 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

munger-worldly-wisdom 用的人多吗?

公开数据是累计安装 1,797 次,近一周安装 72 次,下载 582 次,GitHub 98 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

munger-worldly-wisdom 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
munger-worldly-wisdom

芒格世俗智慧 · 本页

1,79798需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Munger Worldly Wisdom

Apply multidisciplinary mental models to make few, high-conviction decisions within your circle of competence.

When to Use

✅ Use for: Investment decisions, business strategy, complex problem-solving, evaluating competitive advantages, designing incentive systems, long-term capital allocation, avoiding cognitive biases ❌ NOT for: High-frequency trading, technical analysis, single-discipline academic research, speculative opportunities outside competence, situations requiring immediate action without analysis

Core Process

Investment Decision Tree

1. Three-Basket Screen
   ├─ Can I understand this business deeply?
   │  ├─ NO → Reject immediately (pharmaceuticals, complex tech)
   │  ├─ TOO COMPLEX → Reject immediately
   │  └─ YES → Continue to step 2
   │
2. Competitive Moat Assessment
   ├─ Does it have durable competitive advantages?
   │  ├─ Brand strength → Assess psychological lock-in
   │  ├─ Scale economies → Calculate cost advantage
   │  ├─ Network effects → Evaluate switching costs
   │  ├─ Regulatory protection → Check durability
   │  └─ NO MOAT → Reject (commodity business)
   │
3. Business Quality Check
   ├─ Will productivity improvements stay with owners or flow to customers?
   │  ├─ FLOW TO CUSTOMERS → Reject (textile trap)
   │  └─ STAY WITH OWNERS → Continue
   │
4. Intrinsic Value vs. Market Price
   ├─ Calculate free cash flow (not reported earnings)
   ├─ Assess whole business value
   ├─ Does intrinsic value significantly exceed price?
   │  ├─ NO → Wait (no margin of safety)
   │  └─ YES → Continue to step 5
   │
5. Psychological Checklist
   ├─ Am I being influenced by incentive-caused bias?
   ├─ Is social proof driving my judgment?
   ├─ Am I victim of consistency principle (defending past decision)?
   ├─ Could lollapalooza effect (multiple forces) be creating misjudgment?
   │  └─ ANY YES → Re-evaluate objectively
   │
6. Opportunity Cost Comparison
   ├─ Is this the best use of capital vs. alternatives?
   │  ├─ NO → Wait for better opportunity
   │  └─ YES → Continue to step 7
   │
7. Action Decision
   └─ Do ALL factors align perfectly?
      ├─ NO → Do nothing (sit on ass)
      └─ YES → Commit large percentage of capital, hold with zero turnover

Building Worldly Wisdom Tree

1. Identify Big Ideas from Major Disciplines
   ├─ Psychology: cognitive biases, operant conditioning, social proof
   ├─ Economics: competitive advantage, incentives, supply/demand
   ├─ Mathematics: probability, compound interest, permutations
   ├─ Physics: critical mass, equilibrium, relativity
   ├─ Biology: evolution, ecosystem niches, complex systems
   └─ Master 80-90 core models (carry 90% of freight)

2. For Each Problem, Apply Multiple Models
   ├─ What does psychology say?
   ├─ What does economics say?
   ├─ What does mathematics say?
   ├─ What does physics say?
   └─ Where do models reinforce? (lollapalooza check)

3. Inversion Check
   ├─ Think forward: What creates success?
   ├─ Think backward: What guarantees failure?
   └─ Synthesize insights from both directions

4. Disconfirming Evidence Search
   ├─ What would prove this wrong?
   ├─ Am I protecting cherished beliefs?
   └─ Darwin method: spend time trying to disprove own theory

Pre-Decision Checklist

Before any major decision:
☐ Have I applied models from multiple disciplines?
☐ Have I thought this through backward (inversion)?
☐ Am I within my circle of competence?
☐ Have I checked for incentive-caused bias?
☐ Have I sought disconfirming evidence?
☐ Could psychological forces be creating lollapalooza effect?
☐ What's the opportunity cost?
☐ Have I identified what could go wrong?
☐ Is this a one-foot fence with big reward, not seven-foot fence?
☐ Can I wait for better circumstances if anything is uncertain?

Anti-Patterns

Activity Bias Trap

Novice approach: Constant trading and portfolio activity; belief that doing something is always better than doing nothing; inability to sit still.

Expert approach: Make 3-10 major decisions over entire career; practice "sit-on-your-ass investing"; hold positions with virtually zero turnover; wait months or years for perfect opportunity.

Timeline: Novices exhaust themselves in years through trading costs and taxes. Experts compound wealth over decades through patience—Berkshire's success came from handful of decisions over 50+ years.

Shibboleth: "We don't leap seven-foot fences. We look for one-foot fences with big rewards on the other side."


Man-With-Hammer Syndrome

Novice approach: Apply single discipline to every problem; torture reality to fit available models; rely exclusively on specialty training.

Expert approach: Build latticework of 80-90 mental models from 8-10 disciplines; apply multiple lenses to each problem; check for lollapalooza effects where models combine.

Timeline: Single-discipline thinking produces persistent blind spots throughout career. Multidisciplinary fluency takes 10-20 years to build but reveals second-order effects invisible to specialists.

Shibboleth: "To the man with only a hammer, every problem looks like a nail."


Falling in Love with Positions

Novice approach: Defend losing investments due to consistency principle; unable to admit mistakes; sweep big troubles under rug; become emotionally attached to holdings.

Expert approach: Remain situation-dependent and opportunity-driven; write off losses immediately to preserve capital; maintain extreme objectivity like Darwin seeking to disprove own theories.

Timeline: Novices go broke defending mistakes over months/years. Experts cut losses within days/weeks and reallocate to better opportunities.

Shibboleth: "Be willing to write off losses to live to fight again."


Over-Diversification Delusion

Novice approach: Spread capital across 50-200+ stocks; treat diversification as safety; signal lack of conviction through excessive spreading.

Expert approach: Concentrate 50-90% of capital in 3-10 high-conviction positions within circle of competence; recognize portfolio of three great companies provides sufficient safety.

Timeline: Over-diversification compounds to mediocrity over decades. Concentration in quality compounds to extraordinary returns—Berkshire remained 90% in one equity position.

Shibboleth: "It's rational to remain 90% concentrated in one quality equity."


Ignoring Psychological Forces

Novice approach: Make decisions on purely rational basis; ignore incentive-caused bias, social proof, consistency tendency, deprival super-reaction syndrome.

Expert approach: Apply two-track analysis—rational factors AND psychological forces; use psychological checklist; design systems anticipating cognitive limitations.

Timeline: Psychology-blind investors repeat New Coke, LTCM-type disasters throughout career. Psychology-aware investors like Munger identify opportunities others miss (Coca-Cola lollapalooza effect).

Shibboleth: "Very smart people make bonkers mistakes by ignoring psychology."


Learning Only from Personal Experience

Novice approach: Insist on firsthand trial-and-error; dismiss vicarious learning; repeat common disasters like drunk driving analogy.

Expert approach: Learn vicariously through biographies, case studies, history; stand on shoulders of giants; absorb elementary worldly wisdom from $30 history books.

Timeline: Personal-only learning guarantees second-rate achievement over entire career. Vicarious learning compresses centuries of wisdom into years of study.

Shibboleth: "There are answers worth billions of dollars in a $30 history book."

Key Mental Models

Latticework of Mental Models

Framework of fundamental concepts from multiple disciplines creating interconnected structure for hanging experiences. Single models insufficient; need 80-90 core models for worldly wisdom.

Circle of Competence

Boundary separating domains of genuine understanding from areas where others have advantages. Stay within boundaries; expand slowly; admit ignorance confidently.

Lollapalooza Effect

Extreme cascading results when multiple psychological/economic forces operate in same direction simultaneously. Coca-Cola success = operant conditioning + Pavlovian association + social proof + scale economies + distribution advantages.

Inversion (Jacobi)

Solve problems backward: "What guarantees failure?" instead of "What creates success?" Reveals hidden obstacles forward thinking misses. Darwin method: spend time trying to disprove own best-loved theories.

Incentive-Caused Bias

Subconscious distortion of cognition from financial/psychological incentives. Most powerful psychological tendency. Must design systems anticipating it, not rely on moral exhortation.

Competitive Moat

Durable competitive advantages protecting business from rivals: brand strength, network effects, scale economies, switching costs, regulatory protection. Width and durability determine long-term value.

Deprival Super-Reaction Syndrome

Irrational overreaction to loss of something already possessed. New Coke fiasco: consumers valued existing product disproportionately. Makes established brands extraordinarily valuable.

Shibboleths (Expert Recognition Patterns)

  • "Three-basket screen: yes, no, or too tough to understand"
  • "Sit-on-your-ass investing"
  • "Great business at fair price beats fair business at great price"
  • "If facts don't hang together on latticework of theory, you don't have them in usable form"
  • "Getting the incentives right is a very, very important lesson"
  • "Invert, always invert" (Jacobi)
  • "One-legged man in an ass-kicking contest" (lacking numerical fluency)
  • "Mr. Market as manic-depressive fellow offering daily opportunities"
  • "Two-track analysis: rational AND psychological"
  • "Playing bridge by counting trumps while ignoring everything else" (single-discipline thinking)

Historical Evolution

1930s-1960s (Graham Era): Value = stocks below working capital. Quantitative formulas. Post-Depression bargains abundant.

1960s-1980s (Munger-Buffett Shift): Recognition that great businesses at 2-3x book value superior to cheap commodity businesses. Quality > absolute cheapness. Textile experience taught productivity gains flow to customers in commodity industries.

1990s-2000s (Fee Explosion): Institutions shifted to complex fund-of-funds, multiple consultant layers, exotic partnerships. Total costs reached 3% annually. "Febezzlement" through fee layering.

2000s-Present (Multidisciplinary Integration): Growing recognition that academic balkanization harmful. Behavioral economics mainstream. Business schools require psychology. Medical schools teach communication. Hard science organizing ethos applied to soft science.

References

  • Source: Poor Charlie's Almanack by Charles T. Munger (compiled by Peter Kaufman)
  • Core philosophy: Multidisciplinary latticework of mental models for worldly wisdom
  • Partnership context: 50+ years with Warren Buffett at Berkshire Hathaway

平台分布

Codex

34.59%
按下载量换算201

Claude

30.34%
按下载量换算177

Cursor

17.38%
按下载量换算101

Gemini CLI

9.58%
按下载量换算56

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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