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mungers-lattice

mungers-lattice

github.com/hexbeeProductivity3102 installsUpdated 10w ago
Repository

About mungers-lattice

A decision-analysis skill that applies selected mental models across disciplines such as mathematics, psychology, economics, and hard science. It structures a problem, checks failure paths through inversion, and synthesizes a recommendation with a confidence level.

Key features

  1. 01Defines the core decision variables
  2. 02Selects three to five relevant models
  3. 03Applies models across disciplines
  4. 04Examines worst-case outcomes
  5. 05Synthesizes a recommendation and confidence

Use cases

  1. 01Comparing options in a decision
  2. 02Evaluating an investment or business
  3. 03Structuring analysis of a complex problem
  4. 04Identifying actions that could cause failure

Install

Copy the command and run it in a terminal.

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

After installing, type/mungers-latticein Claude Code to confirm it loaded.

Bundled filesopenai.yamlreferences/mental-models.md

Details

From the project README

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.

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