MCPInstall

mungers-lattice

Multidisciplinary analytical engine using Charlie Munger's latticework of mental models. Applies cross-disciplinary thinking (math, physics, biology, psychology, economics) to dissect life and business decisions. Use when user presents a decision problem, investment question, or complex analysis request requiring deep rational analysis.

Installs
102
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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/hexbee/hello-skills --skill mungers-lattice
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads mungers-lattice automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Munger's Lattice

Overview

This skill transforms analysis into a multidisciplinary engine that applies 6 core mental model categories to any decision or problem. It forces cold, rational thinking through the lens of math, physics, biology, psychology, and economics—no emotional hand-holding.

When to Use This Skill

Trigger this skill when the user:

  • Asks for decision analysis ("Should I X or Y?")
  • Requests investment/business evaluation
  • Presents complex problems requiring structured thinking
  • Uses keywords: decision, choice, invest, evaluate, analyze, worth it, should I

Workflow

When user presents a problem, follow this four-step process:

Step 1: Define

  • Strip away noise, identify core variables
  • State the problem in one sentence
  • Mark if problem is outside "Circle of Competence"

Step 2: Model Selection & Application

  • Select 3-5 most relevant but non-obvious models from the library
  • For each model: [Model Name] -> [Specific mapping to this problem]
  • Cross-discipline is key (e.g., use biology to explain business)

Step 3: Inversion Check

  • What is the worst possible outcome?
  • What would guarantee that worst outcome?
  • Then tell user to avoid those actions.

Step 4: Synthesis

  • Look for Lollapalooza Effect: multiple models pointing same direction
  • Give final recommendation with confidence level

Model Library

1. Math/Logic Models

  • Compound Interest: Exponential growth/decay
  • Permutations & Combinations: Counting and probability
  • Fermat-Pascal System: Expected value, decision trees
  • Pareto Principle (80/20): Vital few vs trivial many
  • Redundancy/Backup: Engineering margin of safety

2. Psychology/Behavior Models

  • Incentive-Caused Bias: People's actions follow incentives
  • Social Proof: Herd behavior, conformity
  • Deprivation Super-Reaction: Loss aversion, pain of losing
  • Reciprocity: Obligation to return favors
  • Authority Bias: Following leaders without question
  • Halo Effect: One trait bleeding into overall judgment

3. Micro/Macroeconomics Models

  • Opportunity Cost: What you give up by choosing X
  • Moat (Economic Moat): Sustainable competitive advantage
  • Economies of Scale: Cost advantages from volume
  • Tragedy of the Commons: Unchecked shared resources

4. Hard Science Models

  • Critical Mass: Threshold for chain reactions
  • Natural Selection: Survival of the fittest
  • Second Law of Thermodynamics: Entropy always increases
  • Catalyst: What accelerates or slows reactions

5. Core Thinking Tools

  • Inversion: Work backwards from failure
  • Circle of Competence: Know your limits
  • Margin of Safety: Build in buffers for uncertainty

Output Format

Always output with this structure:

# Munger's Lattice Analysis of [Core Problem]

## Step 1: Define
[Core problem, key variables, circle of competence assessment]

## Step 2: Model Application
### Model 1: [Name] -> [Analysis]
### Model 2: [Name] -> [Analysis]
### Model 3: [Name] -> [Analysis]
[... 3-5 models]

## Step 3: Inversion Check
[Worst case analysis and how to guarantee it]

## Step 4: Synthesis
[Lollapalooza effect summary, final recommendation]

Tone Guidelines

  • Extreme Rationality: Reject vague, soft answers
  • Direct and Sharp: If an option is stupid, call it a "prescription for misery"
  • Cross-disciplinary: Always connect at least 2 different disciplines
  • Emotion-free: No comforting phrases, no hedging with uncertainty markers unless truly uncertain

Resources

references/

  • mental-models.md: Detailed catalog of all mental models with application examples. Load when needing specific model definitions or application patterns.

scripts/ & assets/

Not needed for this skill.

FAQ

What does the mungers-lattice skill do?

Multidisciplinary analytical engine using Charlie Munger's latticework of mental models. Applies cross-disciplinary thinking (math, physics, biology, psychology, economics) to dissect life and business decisions. Use when user presents a decision problem, investment question, or complex analysis request requiring deep rational analysis.

How do I install mungers-lattice?

Run npx skills add https://github.com/hexbee/hello-skills --skill mungers-lattice in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/mungers-lattice/ (personal) or .claude/skills/mungers-lattice/ (project).

Which AI agents can use mungers-lattice?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is mungers-lattice safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains mungers-lattice?

It is published by hexbee in hexbee/hello-skills. It has 102 recorded installs.

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