AI Berkshire

AI Berkshire is an open-source collection of investment-research skills for Claude Code and Codex, published by xbtlin on GitHub. It packages the methodologies of Warren Buffett, Charlie Munger, Duan Yongping and Li Lu into 20 slash-command skills covering company research, earnings analysis, industry screening, portfolio management and thinking tools. The latest listed release is v1.0.0.

What It Is

AI Berkshire is a skill framework that runs inside an AI coding client rather than a standalone application. Users install the skills into Claude Code (as commands) or Codex (as skills and optional slash prompts), then invoke them with a company, industry or report as input. Outputs are structured research reports with scores, pass/gray-zone/fail conclusions and price-range suggestions, written as Markdown files. The README states that the project is for study and research and is not investment advice.

How the Research Workflow Works

Team-type skills such as /investment-team and /earnings-team use a Team Lead that dispatches four parallel agents, one per master's perspective. Each agent searches, cross-checks data and scores independently, and the lead then synthesizes the results. Lighter skills such as /quality-screen and /news-pulse call tools directly for quick screening or price-move attribution. The README describes built-in safeguards: an A/B/C information-richness rating, Munger-style inversion checks, a veto checklist, a contrarian check and an explicit "gray zone" label when data is thin.

Skill Categories

The 20 skills are grouped into deep research (investment-research, investment-team, management-deep-dive, private-company-research, deep-company-series), earnings analysis (earnings-review, earnings-team), industry screening (industry-research, industry-funnel, quality-screen, bottleneck-hunter, era-alpha, investment-checklist), portfolio management (income-investment, portfolio-review, thesis-tracker, thesis-drift, news-pulse) and thinking tools (dyp-ask, financial-data, wechat-article).

Financial Rigor Tooling

A Python tool, tools/financial_rigor.py, handles market-cap verification, valuation checks, multi-source cross-validation, three-scenario valuation, Benford's-law detection and a precise calculator. It uses Python decimal.Decimal rather than floats. The project also documents a cost note: deep research skills consume many tokens, and the maintainers suggest using lighter skills first to screen before running full analyses.