MichaelRochonnn

MichaelRochonnn / buffett-investment-research

Public

Buffett-style company analysis skill for Codex that turns primary-source research into structured investment memos.

41
7
100% credibility
Found Apr 14, 2026 at 41 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A skill and helper tool for AI to produce Warren Buffett-style investment memos analyzing company business quality, moats, management, and valuation from primary sources.

How It Works

1
📰 Discover Buffett Research Tool

You find a helpful guide that lets an AI analyze companies just like Warren Buffett would, focusing on business quality and smart investing.

2
📁 Add to Your AI Helper

You simply place the tool into your AI assistant's special folder so it's ready to use anytime.

3
📊 Grab Company Snapshot (US Stocks)

For American companies, you run a quick lookup to pull official records like reports and key numbers to start your research.

4
💭 Ask for Company Analysis

You tell your AI to evaluate a company or stock using Buffett's principles, like checking the moat, management, and true value.

5
📄 Receive Structured Memo

Your AI creates a clear, step-by-step investment report covering business strength, risks, and a final verdict like 'strong fit' or 'watchlist'.

✅ Make Smarter Choices

You gain deep insights into companies, helping you decide wisely on investments without hype or quick guesses.

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Star Growth

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AI-Generated Review

What is buffett-investment-research?

This Python-based Codex skill turns primary-source research into structured investment memos using a Buffett-style company analysis framework. Feed it a ticker or company name, and it delivers a disciplined report covering moat, management, balance sheet strength, owner earnings, and valuation--with verdicts like "Strong fit," "Watchlist," or "Reject." It solves the problem of shallow AI investment prompts by enforcing a sequence that starts with filings and facts before opinions.

Why is it gaining traction?

Unlike generic prompts that spit out quick buy/sell takes mixed with hype, this enforces a Buffett workflow: primary sources first, hard filters on culture and resilience, and honest "pass" options. Developers dig the repeatable memos for comparing companies on moat durability and capital allocation, plus a bonus Python CLI for instant SEC snapshots on U.S. tickers like AAPL. At 41 stars, it's niche but hooks value-investing enthusiasts tired of EBITDA fluff.

Who should use this?

Value investors scripting Codex for equity research, fintech devs prototyping Buffett screens, or analysts vetting stocks inside their circle of competence. Ideal for quick moat checks on tech giants or consumer plays, or stress-testing cheap valuations with owner-earnings math. Skip if you're into momentum trading or non-U.S. filings without manual tweaks.

Verdict

Solid starter for Buffett-style analysis in Codex setups--great docs and workflow make it instantly usable despite low 1.0% credibility score and 41 stars signaling early maturity. Pair the skill with its SEC CLI for U.S. work; watch for broader market coverage to scale.

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