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munger-observer芒格观察家

Agent Skill

munger-observer 用于补充运维和基础设施相关能力,适合在 Codex、Claude、Cursor、Gemini CLI 中需要让 Agent 承接运维和基础设施相关任务时使用。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。

总安装

27,025

周安装

849

GitHub Stars

177

下载量

6,988
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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-observer(芒格观察家)
来源仓库:https://github.com/moltbot/skills
仓库路径:skills/munger-observer
安装命令:
npx skills add moltbot/skills --skill "munger-observer"
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。

AgentSkills.tonpx skills
npx skills add moltbot/skills --skill "munger-observer"

简介

每日智慧回顾将查理·芒格的心理模型应用到你的工作和思考中。当被要求审查决策、分析思维模式、检测偏见、应用心理模型、进行“芒格审查”或运行芒格观察员时使用。触发预定的每日回顾或手动请求,例如“运行芒格观察者”、“回顾我的想法”、“检查盲点”或“应用心理模型”。

SKILL.md

name
munger-observer
description
Daily wisdom review applying Charlie Munger's mental models to your work and thinking. Use when asked to review decisions, analyze thinking patterns, detect biases, apply mental models, do a "Munger review", or run the Munger Observer. Triggers on scheduled daily reviews or manual requests like "run munger observer", "review my thinking", "check for blind spots", or "apply mental models".

Munger Observer

Automated daily review applying Charlie Munger's mental models to surface blind spots and cognitive traps.

Process

1. Gather Today's Activity

  • Read today's memory file (memory/YYYY-MM-DD.md)
  • Scan session logs for today's activity
  • Extract: decisions made, tasks worked on, problems tackled, user requests

2. Apply Mental Models

Inversion

  • What could go wrong? What's the opposite of success here?
  • "Tell me where I'm going to die, so I'll never go there."

Second-Order Thinking

  • And then what? Consequences of the consequences?
  • Short-term gains creating long-term problems?

Incentive Analysis

  • What behaviors are being rewarded? Hidden incentive structures?
  • "Show me the incentive and I'll show you the outcome."

Opportunity Cost

  • What's NOT being done? Cost of this focus?
  • Best alternative foregone?

Bias Detection

  • Confirmation bias: Only seeking validating information?
  • Sunk cost fallacy: Continuing because of past investment?
  • Social proof: Doing it because others do?
  • Availability bias: Overweighting recent/vivid information?

Circle of Competence

  • Operating within known territory or outside?
  • If outside, appropriate humility/caution?

Margin of Safety

  • What's the buffer if things go wrong?
  • Cutting it too close anywhere?

3. Generate Output

If insights found: 1-2 concise Munger-style observations If nothing notable: "All clear — no cognitive landmines detected today."

Output Format

🧠 **Munger Observer** — [Date]

[Insight 1: Model applied + observation + implication]

[Insight 2 if applicable]

— "Invert, always invert." — Carl Jacobi (Munger's favorite)

Example

🧠 **Munger Observer** — January 19, 2026

**Opportunity Cost Alert:** Heavy focus on infrastructure today. The content queue is aging — are drafts decaying in value while we polish tools?

**Second-Order Check:** Speed improvement is good first-order thinking. Second-order: faster responses may raise expectations for response quality. Speed without substance is a trap.

— "Invert, always invert."

Scheduling (Optional)

Set up a cron job for daily automated review:

  • Recommended time: End of workday (e.g., 5pm local)
  • Trigger message: MUNGER_OBSERVER_RUN

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

62.1%
按下载量换算4,340

Cursor

26.23%
按下载量换算1,833

安全审计

暂无安全审计结果可展示。

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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