New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Munger

by questflowai in questflowai/investorskills

A skill your agent uses when evaluating a decision through Charlie Munger-style mental models: inversion, incentives, quality filters, multidisciplinary reasoning, and concentrated judgment.

MITAuto-check passed

Install Munger

skills CLI
$ npx skills add questflowai/investorskills --skill munger -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install questflowai/investorskills munger --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/questflowai/investorskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/munger .claude/skills/munger && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
munger
GitHub stars
1.9k
Token cost
~618 tokens
SKILL.md length
276 words
Files
2
Skills in repo
63
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when evaluating a decision through Charlie Munger-style mental models: inversion, incentives, quality filters, multidisciplinary reasoning, and concentrated judgment.

  • Works in 6 steps: Invert: ask how this investment could… → Check circle of competence and reject… → Examine incentives and agency problems. → …
  • Evaluating a decision through Charlie Munger-style mental models: inversion
  • SKILL.md covers When To Use, Do Not Use When, Inputs Needed and Process, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Munger is an agent skill from questflowai/investorskills. Use when evaluating a decision through Charlie Munger-style mental models: inversion, incentives, quality filters, multidisciplinary reasoning, and concentrated judgment.

Its SKILL.md is about 620 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `invest.md`).

The repository describes itself as: Investor Skills is an open-source library that turns durable investing judgment into portable, structured formats. It collects how great investors think, filter opportunities… The licence is MIT.

When your agent uses it

  • Evaluating a decision through Charlie Munger-style mental models: inversion
  • Quality filters
  • Multidisciplinary reasoning
  • Concentrated judgment

Example prompts

  • “/munger”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Invert: ask how this investment could fail badly.
  2. Check circle of competence and reject what cannot be understood.
  3. Examine incentives and agency problems.
  4. Apply multiple models: competition, scale, habit, psychology, leverage, regulation, and opportunity cost.
  5. Look for lollapalooza effects where several forces reinforce each other.
  6. Decide whether the answer is obvious enough to justify concentration.

What it can do on your machine

Read from SKILL.md and the folder at commit 2844d78. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Munger loads about 618 tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 276 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~618

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from questflowai/investorskills at commit 2844d78, republished under its MIT licence (© questflowai). 276 words, ~618 tokens.

Download SKILL.mdSave it as .claude/skills/munger/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
munger
description
Use when evaluating a decision through Charlie Munger-style mental models: inversion, incentives, quality filters, multidisciplinary reasoning, and concentrated judgment.
invest
./invest.md

Munger Mental Models

Use this skill to apply Charlie Munger-style judgment: invert the problem, remove obvious stupidity, examine incentives, use multiple mental models, and only act when quality and understanding are unusually high.

When To Use

Use this skill when the user asks for:

  • Mental-model analysis of an investment
  • Inversion and pre-mortem review
  • Incentive and management-quality analysis
  • Whether a decision is inside the circle of competence
  • Concentrated decision review before acting

Trigger phrases include Munger, mental models, inversion, incentives, latticework, circle of competence, and avoid stupidity.

Do Not Use When

  • The user needs a mechanical technical entry.
  • The decision depends on short-term price action only.
  • There is not enough information to understand incentives and business quality.
  • The user wants confirmation of a decision they already made.

Inputs Needed

  • Company or decision context
  • Business model and economics
  • Incentives of management, customers, regulators, and competitors
  • Known risks, unknowns, and failure modes
  • Current valuation or opportunity cost if relevant

Process

  1. Invert: ask how this investment could fail badly.
  2. Check circle of competence and reject what cannot be understood.
  3. Examine incentives and agency problems.
  4. Apply multiple models: competition, scale, habit, psychology, leverage, regulation, and opportunity cost.
  5. Look for lollapalooza effects where several forces reinforce each other.
  6. Decide whether the answer is obvious enough to justify concentration.

Output Format

md
# Munger View: [Decision]

## Verdict
Act / Wait / Pass / Too Hard

## Inversion

## Incentives

## Mental Models Applied

## Quality Filter

## Opportunity Cost

## Biggest Ways This Fails

## Missing Data

Guardrails

  • Do not overcomplicate what should be rejected quickly.
  • Do not ignore incentives.
  • Do not invest outside the circle of competence.
  • Do not mistake intelligence for judgment.
  • Avoid obvious stupidity before seeking brilliance.

Questflow Use

In Questflow, this skill is best used as a decision-quality layer before launching, copying, sizing, or concentrating in a Fund strategy.

© questflowai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/munger of questflowai/investorskills.

  • SKILL.md
  • invest.md

Open the folder on GitHubat commit 2844d78

Compare with similar skills

Munger next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Munger compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Munger this skillquestflowai/investorskills1.9k—~618Automated safety check: PassMIT
Arize Evaluatorgithub/awesome-copilot40k2 repos~8.1kAutomated safety check: NotesMIT
LLM Evaluationdavila7/claude-code-templates32k13 repos~3.5kAutomated safety check: PassMIT
Agent Evaluationsickn33/agentic-awesome-skills47k1 repos~2kAutomated safety check: PassMIT
EvaluatorsArize-ai/phoenix12k—~1.7kAutomated safety check: PassCustom licence
Agent Evaluation Reportingsickn33/agentic-awesome-skills47k1 repos~2.1kAutomated safety check: PassMIT

Similar skills

  • Arize Evaluator

    github/awesome-copilot

    Official

    Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and…

    40k GitHub starsUsed in 2 repos~8.1k tokens
    AI & LLM EngineeringAuto-check: notes

  • LLM Evaluation

    davila7/claude-code-templates

    Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.

    32k GitHub starsUsed in 13 repos~3.5k tokens
    AI & LLM EngineeringAuto-check passed

  • Agent Evaluation

    sickn33/agentic-awesome-skills

    Evaluate agent behavior with versioned cases and explicit verifiers.

    47k GitHub starsUsed in 1 repo~2k tokens
    Agent WorkflowsAuto-check passed

  • Evaluators

    Arize-ai/phoenix

    Author or refine a Phoenix evaluator — code or LLM-as-a-judge — that scores a run's output.

    12k GitHub stars~1.7k tokensUpdated today
    EducationAuto-check passed

  • Agent Evaluation Reporting

    sickn33/agentic-awesome-skills

    A skill your agent uses when summarizing agent evaluations where autonomous, assisted, failed, timed-out, or invalid outcomes must remain distinct and comparable.

    47k GitHub starsUsed in 1 repo~2.1k tokens
    Agent WorkflowsAuto-check passed

  • Creating Online Evaluations

    PostHog/posthog

    Official

    Author continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified.

    40k GitHub stars~6.7k tokensUpdated today
    AI & LLM EngineeringAuto-check passed

More from questflowai/investorskills

All 63 skills in this repo

  • A16z Techno Optimist

    questflowai/investorskills

    A skill your agent uses when evaluating startups or tech platforms through an a16z-style lens: technology adoption, market creation, platform power, AI/crypto/software narratives, and bold…

    1.9k GitHub stars~512 tokensUpdated 1 mo ago
    Auto-check passed

  • Ackman Concentrated Activism

    questflowai/investorskills

    A skill your agent uses when evaluating Bill Ackman-style concentrated long theses, activist campaigns, high-conviction multiyear bets, and public narrative plus fundamental catalysts.

    1.9k GitHub stars~491 tokensUpdated 1 mo ago
    Auto-check passed

  • Ansem Crypto

    questflowai/investorskills

    A skill your agent uses when evaluating crypto narratives, attention rotation, memecoin cycles, Solana-style ecosystem momentum, social distribution, and reflexive retail flows in an Ansem-style…

    1.9k GitHub stars~793 tokensUpdated 1 mo ago
    Auto-check passed

  • Arthur Hayes Liquidity

    questflowai/investorskills

    A skill your agent uses when evaluating crypto markets through an Arthur Hayes-style liquidity lens: dollar liquidity, funding, risk appetite, cycle psychology, and macro-driven crypto positioning.

    1.9k GitHub stars~449 tokensUpdated 1 mo ago
    Auto-check passed

  • Buffett

    questflowai/investorskills

    A skill your agent uses when evaluating a business through Buffett-style ownership, owner earnings, durable moat, management quality, capital allocation, and margin-of-safety judgment.

    1.9k GitHub stars~617 tokensUpdated 1 mo ago
    Auto-check passed

  • Burry Asymmetric Contrarian

    questflowai/investorskills

    A skill your agent uses when evaluating Michael Burry-style contrarian, asymmetric, unpopular trades: deep mispricing, short theses, complex assets, forced consensus errors, and catalyst-driven…

    1.9k GitHub stars~495 tokensUpdated 1 mo ago
    Auto-check passed

Questions about Munger

What does Munger do?

A skill your agent uses when evaluating a decision through Charlie Munger-style mental models: inversion, incentives, quality filters, multidisciplinary reasoning, and concentrated judgment. Munger is an agent skill from questflowai/investorskills. Use when evaluating a decision through Charlie Munger-style mental models: inversion, incentives, quality filters, multidisciplinary reasoning, and concentrated judgment.

When should I use Munger?

Munger fits situations like: evaluating a decision through Charlie Munger-style mental models: inversion; quality filters; multidisciplinary reasoning; concentrated judgment.

How do I install Munger in Claude Code?

Run `npx skills add questflowai/investorskills --skill munger -a claude-code`. Or copy the skill folder (skills/munger in questflowai/investorskills) into .claude/skills/munger in your project. Claude Code loads it when a task matches its description.

How do I install Munger in Codex?

Run `npx skills add questflowai/investorskills --skill munger -a codex`. Or copy the skill folder (skills/munger in questflowai/investorskills) into .agents/skills/munger in your project. Codex loads it when a task matches its description.

Can I use Munger in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add questflowai/investorskills --skill munger -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/munger, .gemini/skills/munger, .github/skills/munger and .opencode/skills/munger in your project.

What does Munger need to run?

SKILL.md names no scripts, command-line tools or credentials: Munger is instructions for the agent only.

Does Munger access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Munger safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Munger use?

Munger is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Munger use?

About 618 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Munger?

Skills that share tags, products or a category with Munger: Arize Evaluator (github/awesome-copilot, 40k stars), LLM Evaluation (davila7/claude-code-templates, 32k stars), Agent Evaluation (sickn33/agentic-awesome-skills, 47k stars) and Evaluators (Arize-ai/phoenix, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Munger?

questflowai (a GitHub organization) maintains it in questflowai/investorskills, which has 1,896 GitHub stars. The repository holds 63 skills in this directory. The repository was last updated on August 23, 2026.

Source: questflowai/investorskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.