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Buffett Investment Research

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MichaelRochonnn
buffett-investment-research

Buffett-style company analysis and value-investing research. Use when Codex needs to analyze a business or listed company with Warren Buffett's framework, including 巴菲特框架, 价值投资, 护城河, 管理层, 企业文化, 资本配置, 财务韧性, 回购, 错误复盘, 危机应对, or when asked for a Buffett-style investment memo or recommendation.

Overview

PublisherMichaelRochonnn
Repositorybuffett-investment-research
Skill namebuffett-investment-research
Stars
65
Forks
15
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by MichaelRochonnn on GitHub. Read the source before you install it.

Installation

Install the Buffett Investment Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/MichaelRochonnn/buffett-investment-research/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/MichaelRochonnn/buffett-investment-research.git \
  .claude/skills/buffett-investment-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Buffett Investment Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Buffett Investment Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Buffett Investment Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Buffett Investment Research

Use this skill to produce a Buffett-style research memo, not a hot take. The goal is to judge business quality, management quality, capital allocation, balance-sheet resilience, reinvestment runway, and price discipline.

Treat the output as decision support rather than personalized financial advice. Give a framework-based verdict, state assumptions plainly, and make uncertainty visible.

Workflow

  1. Define the company clearly. Confirm the exact entity, ticker, exchange, geography, business mix, and whether the business is within the current circle of competence.

  2. Gather primary sources first. Always browse for current analysis because filings, prices, management teams, leverage, and capital allocation can change.

  3. For U.S. issuers, start with the SEC helper script. Run python3 /Users/fane/.codex/skills/buffett-investment-research/scripts/sec_company_snapshot.py "Company or Ticker".

  4. For non-U.S. issuers, start with official sources. Prioritize the investor-relations site, annual report, exchange filings, regulator filings, proxy or AGM materials, and earnings-call transcripts.

  5. Read the local references in this order. Start with references/framework.md. Then read references/memo-template.md. Read references/timeline.md when the user asks for deeper philosophical context, historical evolution, Buffett's mistakes, or crisis playbooks.

  6. Write the memo. Judge the business first, then the price. Do not start from the chart.

Source Priority

  • Official annual reports, 10-K or equivalent, proxy, regulator filings
  • Official earnings-call transcripts, investor presentations, and capital-markets materials
  • Competitor filings and industry disclosures
  • Credit-rating commentary, regulator data, and trustworthy trade sources
  • Secondary commentary only after primary-source facts are pinned down

Buffett Rules To Preserve

  • Analyze a stock as a partial ownership interest in a business.
  • Do not forecast the market, macro cycle, rates, or FX unless the company is directly exposed and the exposure is contractual or balance-sheet based.
  • Prefer simple and durable businesses over complicated stories.
  • Reject businesses outside the circle of competence instead of forcing a verdict.
  • Distinguish business quality from price attractiveness.
  • Reject weak culture, aggressive accounting, or fragile financing even when valuation appears cheap.
  • Prefer patience over false precision. Pass is a valid answer.

Hard Filters

Reject or downgrade sharply when one of these is true:

  • The business model cannot be explained simply
  • Economics depend on commodity pricing with no durable edge
  • The company needs continuous external capital to survive
  • Leverage or refinancing risk can impair permanent capital
  • Management lacks candor or capital-allocation discipline
  • Industry change is too fast to estimate normalized economics
  • The thesis only works if a greater fool pays more later

Output Requirements

Use the structure in references/memo-template.md. Always include:

  • Circle-of-competence judgment
  • Moat assessment with concrete evidence
  • Management and culture assessment
  • Capital-allocation assessment
  • Balance-sheet and crisis-resilience assessment
  • Valuation logic using normalized owner earnings or a conservative proxy
  • A clear verdict: Strong fit, Watchlist, Weak fit, Reject, or Outside competence
  • A confidence level and the top missing facts that could change the conclusion
  • Source links

Notes On Recommendations

If the user asks whether to invest, answer in Buffett-style language:

  • Say what kind of business this is
  • Say whether it appears to have a durable moat
  • Say whether management acts like owner-operators or empire builders
  • Say whether the balance sheet can survive stress
  • Say whether the price implies an attractive prospective return
  • State the main reasons to pass even if the company is excellent

Never pretend certainty. If the business is good but the price is not, say so plainly.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Buffett Investment Research AI skill do?

Buffett-style company analysis and value-investing research. Use when Codex needs to analyze a business or listed company with Warren Buffett's framework, including 巴菲特框架, 价值投资, 护城河, 管理层, 企业文化, 资本配置, 财务韧性, 回购, 错误复盘, 危机应对, or when asked for a Buffett-style investment memo or recommendation.

Why use Buffett Investment Research on TypingMind?

Because you install it once and use it with any model. Buffett Investment Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Buffett Investment Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MichaelRochonnn/buffett-investment-research/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Buffett Investment Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Buffett Investment Research?

As many as you like. As long as a model supports skills, you can use Buffett Investment Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Buffett Investment Research AI skill free?

Yes. It is published on GitHub by MichaelRochonnn under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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