Charlie Munger - Inversion Thinking

Charlie Munger - Inversion Thinking is a skill for Claude Code, Codex from OpenLabor/openlabor. It costs 58 tokens per session (2,039 once invoked), scanned A, original, MIT.

A decision-review method that starts by asking how a plan could fail, then uses a pre-mortem—a forecast of failure before it happens—and checklists to reduce mistakes.

In plain words
What is it for?
Use it to pressure-test plans, analyze possible failures, identify cognitive biases, and create checklists for important decisions.
Why use it?
It helps expose risks, blind spots, and thinking errors before they become expensive problems.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to pressure-test plans, analyze possible failures, identify cognitive biases, and create checklists for important decisions.

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Install with agentmods
npx agentmods add skills/openlabor/openlabor/charlie-inversion-thinking
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add OpenLabor/openlabor --skill charlie-inversion-thinking
Clone the repo
git clone --depth 1 https://github.com/OpenLabor/openlabor

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for Charlie Munger - Inversion Thinking

README.md
[![agentmods](https://agentmods.dev/badge/skills/openlabor/openlabor/charlie-inversion-thinking.svg)](https://agentmods.dev/skills/openlabor/openlabor/charlie-inversion-thinking)
Your own site
<a href="https://agentmods.dev/skills/openlabor/openlabor/charlie-inversion-thinking"><img src="https://agentmods.dev/badge/skills/openlabor/openlabor/charlie-inversion-thinking.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,039 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00058 $0.02039
Opus 5 $0.00029 $0.01019
Sonnet 5 $0.00012 $0.00408
Haiku 4.5 $0.00006 $0.00204

Measured 8d ago against content hash a28361fd4c44, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

Charlie Munger - Inversion Thinking scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/charlie-inversion-thinking/SKILL.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Charlie Munger - Inversion Thinking

Munger's inversion framework teaches that the path to success runs through aggressively avoiding failure. Instead of asking "how do I succeed?" ask "what would guarantee failure, and how do I avoid those things?"

Routes when user asks about: inversion thinking, avoiding mistakes, pre-mortem, cognitive biases, checklist thinking, how to avoid stupidity, reverse engineering success, failure analysis, decision-making errors


Phase 1: Context Gathering

Before applying any framework, understand the situation:

  1. Ask the user: "What decision, plan, or goal are you currently working on that you'd like me to help you pressure-test through inversion?"
  2. Read any relevant context the user provides — business description, current strategy, upcoming launch, investment thesis, or organizational change.

Phase 2: Diagnostic Questions

Ask these questions ONE AT A TIME. Wait for each answer before asking the next. Adapt based on answers — skip questions that have already been answered.

  1. "Walk me through the plan as it stands today — what does success look like, and what's the timeline?"
  2. "If this fails spectacularly 12 months from now, what's the most likely reason? What's your gut telling you?"
  3. "Who are the key people involved, and are their incentives aligned with the outcome you want?"
  4. "What's the one assumption in this plan that, if wrong, would make everything else fall apart?"
  5. "Have you gotten honest pushback from anyone — someone who told you this might not work? What did they say?"

Maximum 5 questions. Stop early if you have enough to work with.


Phase 3: Analysis

Apply Munger's frameworks to the user's specific situation:

The Inversion Protocol

Apply this step by step to the user's stated goal:

Step 1 — State the Goal Clearly: Restate what the user told you success looks like. Be specific.

Step 2 — Invert (List Everything That Would Guarantee Failure): Brainstorm aggressively. Ask: "If I wanted this to fail spectacularly, what would I do?" Generate at least 8-10 failure modes. Categories to cover:

  • People failures: wrong team, misaligned incentives, key person left
  • Market failures: wrong customer, too small a market, bad timing
  • Execution failures: too slow, too expensive, quality problems
  • External failures: regulatory change, new competitor, economic shock
  • Resource failures: ran out of cash, couldn't hire, supply chain issue

Read the full file on GitHub · 168 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 168 lines · 58 tokens per session scan A a28361fd4c44

Subscribe to this mod's changes

Charlie Munger - Inversion Thinking is a skill published in the GitHub repository OpenLabor/openlabor (4 stars, last pushed 7d ago), licensed MIT. It adds 58 tokens to every session and 2,039 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.