hexbee/hello-skills

mungers-lattice

Multidisciplinary analytical engine using Charlie Munger's latticework of mental models.

First seen Jan 26, 2026

Installation

$ npx skills add hexbee/hello-skills --skill mungers-lattice

Summary

  • 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.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
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GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 2
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,203 B
  • docs SUMMARY.md 361 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 103 installs

SKILL.md

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.