# AI-Berkshire Agent Setup Documentation: Complete Installation Guide > Find complete AI-Berkshire agent setup documentation in the xbtlin/ai-berkshire repository. This guide covers installation, Claude Code, and OpenAI Codex skills. - Repository: [Xbt Lin/ai-berkshire](https://github.com/xbtlin/ai-berkshire) - Tags: documentation - Published: 2026-07-01 --- **AI-Berkshire agent setup documentation is located in the repository's [`README.md`](https://github.com/xbtlin/ai-berkshire/blob/main/README.md) and automated installer scripts, supporting both Claude Code commands and OpenAI Codex skills through a language-agnostic workflow.** The xbtlin/ai-berkshire repository provides platform-specific shell scripts that handle the entire installation process, from CLI prerequisites to skill synchronization. ## Prerequisites and Installation Options AI-Berkshire supports two primary LLM platforms. Choose the installation path that matches your preferred coding assistant. ### Claude Code CLI Installation Before running the AI-Berkshire setup, install the Anthropic CLI globally: ```bash npm install -g @anthropic-ai/claude-code ``` This command installs the `claude` binary required to execute the repository's custom commands. ### OpenAI Codex CLI Installation For Codex users, install the CLI using one of three methods supported by the documentation: ```bash # Option 1: curl script curl -fsSL https://chatgpt.com/codex/install.sh | sh # Option 2: npm npm install -g @openai/codex # Option 3: Homebrew brew install openai-codex ``` Verify installation with `codex --version` before proceeding to the repository setup. ## Step-by-Step AI-Berkshire Agent Setup Once the base CLI is installed, configure the agent capabilities through the repository's automation scripts. ### Clone the Repository Clone the canonical source and navigate to the project root: ```bash git clone https://github.com/xbtlin/ai-berkshire.git cd ai-berkshire ``` The `skills/*.md` files in this directory serve as the canonical source definitions for all agent behaviors. ### Run the Platform-Specific Installer Execute the appropriate installer script based on your CLI choice: **For Claude Code users:** ```bash ./scripts/install-claude-commands.sh ``` This script copies the Skill Markdown files into the global Claude Code commands directory, making them available as slash commands. **For Codex users:** ```bash ./scripts/install-codex-skills.sh ``` Optionally, add slash-prompt compatibility: ```bash ./scripts/install-codex-prompts.sh ``` The [`scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-skills.sh) generates and installs the Codex skill packages, while [`scripts/install-codex-prompts.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-prompts.sh) creates wrappers for slash-prompt compatibility. ### Synchronize Generated Artifacts After editing any `skills/*.md` file or pulling updates, regenerate the platform-specific artifacts: ```bash # Refresh Codex skill packages python3 scripts/sync-codex-skills.py # Refresh slash-prompt wrappers (if using optional compatibility layer) python3 scripts/sync-codex-prompts.py ``` These Python scripts treat the Markdown skill definitions as the single source of truth, ensuring consistency across both platforms. ## Verifying Your Installation Confirm the setup completed successfully: - **Claude Code**: Run `claude --version` to verify the CLI version, then list available commands to see the installed skills. - **Codex**: Run `codex --version`, then restart the Codex application to load the newly installed skills into the prompt context. Both platforms should now recognize the 18+ research skills defined in the `skills/` directory. ## Running Your First Agent Invoke agents using platform-specific syntax after completing the AI-Berkshire agent setup. **Claude Code syntax:** ```bash /investment-research 腾讯 /investment-team 美团 /dyp-ask "拼多多的护城河到底在哪里？" ``` **Codex syntax:** After restarting the application, type the skill name directly: ```text investment-research 腾讯 earnings-review PDD 2025Q4 news-pulse 腾讯 ``` Each command automatically spins up four parallel sub-agents that perform distinct analyses—**business model**, **valuation**, **moat**, and **risk**—then aggregate the results into a unified response. ## Understanding the Agent Architecture The underlying architecture is documented in `assets/architecture.mmd`, a Mermaid diagram illustrating how the coordinator agent dispatches parallel sub-agents. When you invoke a skill, the system leverages [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) for financial validation utilities that ensure consistent, quantitative analysis across all sub-agents. This multi-agent design, implemented in the xbtlin/ai-berkshire source code, ensures comprehensive coverage of investment research dimensions without manual prompt engineering. ## Summary - **AI-Berkshire agent setup documentation** resides primarily in [`README.md`](https://github.com/xbtlin/ai-berkshire/blob/main/README.md) and the `scripts/` directory. - Installers at [`scripts/install-claude-commands.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-claude-commands.sh) and [`scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-skills.sh) automate platform-specific setup. - Canonical skill definitions live in `skills/*.md` and are synchronized via [`scripts/sync-codex-skills.py`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/sync-codex-skills.py). - The architecture uses four parallel sub-agents (business, valuation, moat, risk) coordinated through a multi-agent system. - Verification requires CLI version checks and a restart to load newly installed skills. ## Frequently Asked Questions ### Where is the official AI-Berkshire agent setup documentation located? The official documentation is located in the repository's [`README.md`](https://github.com/xbtlin/ai-berkshire/blob/main/README.md) file at the root of the xbtlin/ai-berkshire repository. Additional implementation details are found in the shell scripts within the `scripts/` directory, including [`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), which contain the executable setup instructions. ### Can I use AI-Berkshire with both Claude Code and OpenAI Codex simultaneously? Yes. The repository supports both platforms through separate installer scripts. Run [`./scripts/install-claude-commands.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/./scripts/install-claude-commands.sh) for Claude Code integration and [`./scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/./scripts/install-codex-skills.sh) for Codex. The `skills/*.md` files serve as the single source of truth, so you can maintain both installations and synchronize them using the respective Python sync scripts. ### What happens if I modify a skill definition after installation? After editing any file in `skills/*.md`, you must regenerate the platform artifacts. Run `python3 scripts/sync-codex-skills.py` to refresh Codex skill packages, and for Codex slash-prompt compatibility, run `python3 scripts/sync-codex-prompts.py`. Claude Code users typically do not need synchronization as the installer copies Markdown files directly. ### How do the AI-Berkshire agents handle complex financial analysis? According to the `assets/architecture.mmd` diagram and [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) implementation, each agent invocation spawns four parallel sub-agents specializing in business model analysis, valuation, competitive moat assessment, and risk evaluation. These sub-agents execute simultaneously and aggregate their findings, with financial rigor enforced through shared validation utilities in the `tools/` directory.