# How to Clone the AI Berkshire Repository and Install AI Investment Skills

> Clone the AI Berkshire repository at xbtlin/ai-berkshire and install AI investment skills. Integrate 18 research skills with Claude Code or Codex for enhanced trading.

- Repository: [Xbt Lin/ai-berkshire](https://github.com/xbtlin/ai-berkshire)
- Tags: how-to-guide
- Published: 2026-06-27

---

**Clone the AI Berkshire repository using `git clone https://github.com/xbtlin/ai-berkshire.git`, then run the installation scripts to integrate the 18 investment-research skills with Claude Code or Codex.**

AI Berkshire is a modular, AI-driven investment-research framework developed by xbtlin that organizes its functionality into three distinct layers. Because the project uses only standard-library Python, you can clone the repository and immediately begin using its finance-grade research capabilities without managing external dependencies.

## Cloning the Repository

Start by cloning the repository from GitHub and navigating into the project directory:

```bash
git clone https://github.com/xbtlin/ai-berkshire.git
cd ai-berkshire

```

The project is fully self-contained, requiring no external Python packages or complex environment setup.

## Installing Skills for Your AI Assistant

Once cloned, choose the installation script that matches your AI assistant. The repository provides three helper scripts in the `scripts/` directory to integrate the 18 canonical skills defined in `skills/`.

### Claude Code Setup

To install the skills as Claude Code commands, run the bash script that copies the skill markdown files into Claude Code's global command directory:

```bash
./scripts/install-claude-commands.sh

```

This script copies the canonical definitions from the `skills/` directory (such as [`skills/investment-research.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/investment-research.md)) into Claude Code's global command directory, making commands like `/investment-research` and `/industry-funnel` available immediately.

### Codex Setup

For Codex users, generate and install the skill packages under `~/.codex/skills` using:

```bash
./scripts/install-codex-skills.sh

```

This script generates Codex skill packages from the `skills/` markdown files and installs them in the appropriate local directory.

### Optional Slash Prompt Compatibility

To enable a Claude-style slash-prompt experience within Codex, install the optional compatibility layer:

```bash
./scripts/install-codex-prompts.sh

```

## Understanding the Repository Architecture

The AI Berkshire framework organizes functionality into three layers defined in the source code:

- **Skill layer**: Contains 18 canonical skills stored as markdown files in the `skills/` directory. These define *what* the system does, including flagship commands like `/investment-research`, `/industry-funnel`, and `/news-pulse`. The [`skills/investment-research.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/investment-research.md) file serves as the canonical definition for deep-research workflows.

- **Agent layer**: Each skill internally spawns four independent agents that perform full research sub-tasks (business model, valuation, risk, and synthesis) before returning results to a "Team Lead" for aggregation. This multi-agent workflow is documented in [`AGENTS.md`](https://github.com/xbtlin/ai-berkshire/blob/main/AGENTS.md).

- **Tool layer**: Provides finance-grade rigor through [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py), which implements exact decimal arithmetic, market-cap verification, cross-source validation, and Benford-law checks. All skills automatically invoke this toolkit to verify data before generating reports.

## Executing Your First Research Command

After installation, invoke a skill directly from your terminal. In Claude Code, use the slash command syntax:

```bash
/investment-research 腾讯

```

For Codex installations, use the natural language invocation:

```text
使用 investment-research 研究腾讯

```

The skill automatically calls the [`financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/financial_rigor.py) toolkit to verify market capitalization, valuation ratios, and cross-source data consistency before producing a structured research report.

## Summary

- Clone the AI Berkshire repository using `git clone https://github.com/xbtlin/ai-berkshire.git` — no external dependencies required.
- Install Claude Code commands using [`./scripts/install-claude-commands.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/./scripts/install-claude-commands.sh) or Codex skills using [`./scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/./scripts/install-codex-skills.sh).
- The framework organizes 18 skills in the `skills/` directory across three layers: Skill (definitions), Agent (multi-agent workflow defined in [`AGENTS.md`](https://github.com/xbtlin/ai-berkshire/blob/main/AGENTS.md)), and Tool ([`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py)).
- Each skill spawns four agents (business model, valuation, risk, and team lead) to perform comprehensive investment research.
- Skills automatically validate financial data using exact decimal arithmetic and cross-source verification before generating outputs.

## Frequently Asked Questions

### Do I need external dependencies to run AI Berkshire?

No. AI Berkshire is built using only Python standard library modules. The repository is fully self-contained, so once you clone it and run the appropriate installation script, you can immediately issue skill commands without installing additional packages or managing virtual environments.

### What is the difference between the Claude Code and Codex installation scripts?

[`scripts/install-claude-commands.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-claude-commands.sh) copies the markdown skill definitions from the `skills/` directory into Claude Code's global command directory, enabling native slash commands. [`scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-skills.sh) generates Codex-specific skill packages from the same source files and installs them under `~/.codex/skills`. Both scripts reference the same canonical definitions in `skills/` to ensure consistency across platforms.

### How does the multi-agent system work within each skill?

According to the [`AGENTS.md`](https://github.com/xbtlin/ai-berkshire/blob/main/AGENTS.md) file in the repository, each skill internally instantiates four independent agents that each perform a complete research sub-task: business model analysis, valuation, risk assessment, and final synthesis. These agents operate independently before returning their outputs to a "Team Lead" agent that aggregates the results into a cohesive research report.

### Can I use AI Berkshire without installing the skills globally?

Yes. While the installation scripts ([`install-claude-commands.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/install-claude-commands.sh) and [`install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/install-codex-skills.sh)) provide convenience by registering commands globally, you can manually invoke the skills by referencing the markdown definitions in the `skills/` directory directly or by importing the [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) utilities into your own Python scripts. The repository is designed to function as a standalone reference implementation regardless of installation method.