# How to Set Up the AI Berkshire Environment: A Complete Installation Guide > Set up the AI Berkshire environment with this complete installation guide. Clone the repo, install an AI client like Claude Code or OpenAI Codex, and run scripts to deploy the skill layer. - Repository: [Xbt Lin/ai-berkshire](https://github.com/xbtlin/ai-berkshire) - Tags: how-to-guide - Published: 2026-06-28 --- **Clone the repository, install your preferred AI client (Claude Code or OpenAI Codex), and run the installation scripts to deploy the skill layer.** The AI Berkshire project (`xbtlin/ai-berkshire`) implements a three-layer architecture that separates **Skills**, **Agents**, and **Tools** to provide investment research capabilities through AI assistants. Setting up the environment requires configuring the skill layer to communicate with either Claude Code or Codex clients, enabling parallel agent execution for financial analysis. ## Prerequisites Before installing the AI Berkshire environment, ensure you have the following: - **Node.js** (for Claude Code or Codex CLI installation) - **Python 3** (for running the Codex skill synchronization scripts) - **Git** (to clone the repository) The repository supports two primary client interfaces: **Claude Code** (`@anthropic-ai/claude-code`) and **OpenAI Codex** (`@openai/codex`). You only need to install one to interact with the system. ## Step-by-Step Installation Guide ### Clone the Repository Start by cloning the GitHub repository and navigating into the project directory: ```bash git clone https://github.com/xbtlin/ai-berkshire.git cd ai-berkshire ``` ### Install the AI Client Choose and install your preferred client interface: **For Claude Code users:** ```bash npm install -g @anthropic-ai/claude-code ``` **For Codex users:** ```bash # Option 1: Using the official installer curl -fsSL https://chatgpt.com/codex/install.sh | sh # Option 2: Using npm npm install -g @openai/codex # Option 3: Using Homebrew (macOS) brew install --cask codex ``` ### Deploy the Skill Layer The skill layer consists of human-readable markdown files under `skills/` that define concrete entry points like `/investment-research` and `/quality-screen`. **For Claude Code:** Run the installation script to copy the markdown-based skill definitions into the global Claude Code command directory: ```bash ./scripts/install-claude-commands.sh ``` **For Codex:** First, the system regenerates the Codex skill packages from the canonical `skills/` sources using [`scripts/sync-codex-skills.py`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/sync-codex-skills.py), then installs them: ```bash ./scripts/install-codex-skills.sh ``` This script automatically generates the Codex-compatible skill packages in `codex-skills/**/SKILL.md` from the source files in `skills/`. ### Optional Codex UI Enhancements To get a Claude-like slash-command interface within Codex, install the optional prompt definitions: ```bash ./scripts/install-codex-prompts.sh ``` This copies the markdown prompt files from `codex-prompts/*.md` into the appropriate configuration directory. ## Verifying Your Setup Confirm the installation by checking your client version: ```bash # Claude Code claude --version # Codex codex --version ``` Test the skill invocation with a sample command: ```bash # Claude Code syntax /investment-research 腾讯 # Codex syntax (after client restart) investment-research 腾讯 ``` When you invoke a skill, the **Agent Layer** activates four independent AI agents running in parallel, each adopting a different "master-investor" perspective (巴菲特, 芒格, 段永平, 李录). These agents gather data and return judgments that a Team-Lead agent aggregates. The **Tool Layer** in `tools/`—including [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py)—provides reproducible calculations using Python's `decimal.Decimal` to avoid floating-point errors during market-cap verification and valuation checks. ## Summary - **AI Berkshire** (`xbtlin/ai-berkshire`) uses a three-layer architecture separating Skills, Agents, and Tools for investment research. - **Installation** requires cloning the repo, installing either Claude Code or Codex, and running the appropriate installation script ([`scripts/install-claude-commands.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-claude-commands.sh) or [`scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-skills.sh)). - **Skill files** are defined in `skills/*.md` and automatically synchronized to Codex format via [`scripts/sync-codex-skills.py`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/sync-codex-skills.py). - **Verification** involves testing skill commands like `/investment-research` or `investment-team` followed by a company name. - **Core utilities** in [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) ensure precise financial calculations using `decimal.Decimal`. ## Frequently Asked Questions ### Do I need to install both Claude Code and Codex? No, you only need one client. The repository supports both **Claude Code** and **OpenAI Codex** as interchangeable entry points. Choose the client that matches your AI subscription and install the corresponding skills using either [`scripts/install-claude-commands.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-claude-commands.sh) or [`scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-skills.sh). ### What is the difference between the skills in `skills/` and `codex-skills/`? The `skills/` directory contains the canonical human-readable markdown definitions that serve as the source of truth. The `codex-skills/` directory contains auto-generated packages created by [`scripts/sync-codex-skills.py`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/sync-codex-skills.py) specifically for the Codex client format. You should edit files in `skills/` only; the sync script handles the transformation. ### Why does the tool layer use `decimal.Decimal` instead of float? According to the source code in [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py), the **Tool Layer** uses Python's `decimal.Decimal` for all numeric calculations to maintain exact precision. This prevents floating-point rounding errors that could occur during financial validations like market-cap verification or valuation ratio calculations, ensuring reproducible results. ### Can I use the slash prompts without installing the full skill set? No, the slash prompts in `codex-prompts/*.md` are optional UI enhancements that work alongside the main skill layer. They provide a Claude-like interface for Codex users, but you must still run [`scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-skills.sh) to install the actual skill functionality that invokes the agent layer and tool utilities.