# What Are the Available Skills in AI Berkshire? A Complete Guide to the I-6 Framework

> Discover AI Berkshire's six core I-6 skills: investment research, industry research, financial data, earnings, portfolio, and bottleneck hunter. Master your investment workflow with this comprehensive guide.

- Repository: [Xbt Lin/ai-berkshire](https://github.com/xbtlin/ai-berkshire)
- Tags: getting-started
- Published: 2026-07-10

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**AI Berkshire provides six core "I-6" skills—`/investment-research`, `/industry-research`, `/financial-data`, `/earnings-review`, `/portfolio-review`, and `/bottleneck-hunter`—that form a complete investment research workflow defined in Markdown under `skills/` and synchronized to `codex-skills/`.**

The available skills in AI Berkshire power an end-to-end investment research engine housed in the `xbtlin/ai-berkshire` repository. These skills ship as plain-text Markdown specifications that define exact workflows, data validation rules, and CLI commands for rigorous financial analysis. Each skill is designed to be composable, allowing users to chain together research tasks while enforcing a "two-source, <1% error" data discipline.

## The Six I-6 Skills Available in AI Berkshire

AI Berkshire organizes its capabilities into six distinct skill packages, each accessible via a slash command. These skills are located in `skills/*.md` and mirrored as Codex-compatible packages in `codex-skills/*/SKILL.md`.

### `/investment-research`

**Full-cycle research** using the four investment masters (Buffett, Munger, Duan Yong-ping, Li Lu). This skill drives comprehensive equity analysis by applying multi-master mental models to individual securities. The source definition lives in [`skills/investment-research.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/investment-research.md) and generates [`codex-skills/investment-research/SKILL.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-skills/investment-research/SKILL.md).

### `/industry-research`

**Industry-level analysis** including market-size sizing and "civilization-evolution" framing. Use this skill to assess secular trends and competitive dynamics across sectors. Defined in [`skills/industry-research.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/industry-research.md) with its Codex counterpart at [`codex-skills/industry-research/SKILL.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-skills/industry-research/SKILL.md).

### `/financial-data`

**Data extraction and rigorous verification** of financial numbers. This skill enforces the dual-source verification rule (US equities: Macrotrends + StockAnalysis; HK equities: AASTocks + Macrotrends; CN equities: Eastmoney + 巨潮). It invokes [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) for exact-arithmetic calculations to eliminate LLM "mental math" errors. Source: [`skills/financial-data.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/financial-data.md).

### `/earnings-review`

**Deep earnings-report reading** with data reconciliation and post-earnings commentary. This skill cross-validates transcript data against filings and generates audit trails. Source file: [`skills/earnings-review.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/earnings-review.md).

### `/portfolio-review`

**Portfolio-level monitoring**, risk aggregation, and rebalancing recommendations. This skill aggregates holdings data to assess concentration risk and correlation exposure. Defined in [`skills/portfolio-review.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/portfolio-review.md).

### `/bottleneck-hunter`

**Global supply-chain bottleneck detection** and arbitrage opportunity scouting. Use this skill to identify capacity constraints and supply shortages across global markets. Source: [`skills/bottleneck-hunter.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/bottleneck-hunter.md).

## Skill Architecture and Implementation

Understanding how AI Berkshire structures these skills reveals how the repository maintains consistency between human-readable documentation and executable automation.

### Skill Definition Format

Each skill is a plain-text Markdown file under `skills/` that describes:
- The exact workflow steps
- Required data sources and validation procedures
- CLI command specifications (e.g., calls to [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py))

### Codex Generation Pipeline

The repository uses [`scripts/sync-codex-skills.py`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/sync-codex-skills.py) to read the canonical Markdown sources and render **Codex-compatible** packages. This synchronization ensures that Claude Code and Codex users receive identical skill definitions in `codex-skills/<skill>/SKILL.md`.

### Tooling Backbone

Core Python utilities under `tools/` enforce the Financial Data Discipline:
- **[`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py)**: Performs exact-arithmetic verification of market-cap calculations, valuation metrics, and financial ratios
- **[`tools/report_audit.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/report_audit.py)**: Generates embedded audit tables for reproducibility and traceability

### Workflow Orchestration

Skills are designed to be **composable**. For example, invoking `/investment-research` internally chains `/financial-data` and `/earnings-review` to gather and cross-validate data before producing a final report. This modularity ensures that data integrity rules propagate through every research operation.

## How to Invoke AI Berkshire Skills

After installing the repository via [`scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-skills.sh), interact with the I-6 skills through the `ai-berkshire` CLI. Each command produces a Markdown report containing embedded audit tables generated by [`tools/report_audit.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/report_audit.py).

```bash

# Run full investment research on a US ticker

ai-berkshire /investment-research --ticker AAPL

# Analyze the semiconductor industry

ai-berkshire /industry-research --sector semiconductor

# Pull and validate financial data for a Chinese A-share

ai-berkshire /financial-data --ticker 600519

# Review latest earnings for a US stock

ai-berkshire /earnings-review --ticker MSFT

# Generate portfolio health check

ai-berkshire /portfolio-review --holdings portfolio.csv

# Scan for AI hardware supply chain bottlenecks

ai-berkshire /bottleneck-hunter --focus AI

```

Each execution creates a Markdown report in the working directory with links back to the originating skill definition for full traceability.

## Key Files Supporting the I-6 Skills

| Category | File Path | Purpose |
|----------|-----------|---------|
| **Skill Sources** | [`skills/investment-research.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/investment-research.md) | Four-master research workflow |
| | [`skills/industry-research.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/industry-research.md) | Industry analysis framework |
| | [`skills/financial-data.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/financial-data.md) | Data-source specifications |
| | [`skills/earnings-review.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/earnings-review.md) | Earnings ingestion logic |
| | [`skills/portfolio-review.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/portfolio-review.md) | Portfolio monitoring rules |
| | [`skills/bottleneck-hunter.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/bottleneck-hunter.md) | Supply-chain detection |
| **Generated Packages** | `codex-skills/*/SKILL.md` | Codex compatibility layer |
| **Tools** | [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) | Exact-arithmetic verification |
| | [`tools/report_audit.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/report_audit.py) | Report auditing |
| **Scripts** | [`scripts/sync-codex-skills.py`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/sync-codex-skills.py) | Skill synchronization |
| **Metadata** | [`AGENTS.md`](https://github.com/xbtlin/ai-berkshire/blob/main/AGENTS.md) | Layout and compatibility standards |

## Summary

- **AI Berkshire offers six I-6 skills**: `/investment-research`, `/industry-research`, `/financial-data`, `/earnings-review`, `/portfolio-review`, and `/bottleneck-hunter`.
- **Each skill exists as Markdown** in `skills/` and is synchronized to `codex-skills/` via [`scripts/sync-codex-skills.py`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/sync-codex-skills.py).
- **Data integrity is enforced** through [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) and dual-source verification rules specified in [`skills/financial-data.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/financial-data.md).
- **Skills are composable**, allowing complex research workflows that chain multiple capabilities while maintaining audit trails via [`tools/report_audit.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/report_audit.py).

## Frequently Asked Questions

### How do I access the available skills in AI Berkshire?

Install the repository using [`scripts/install-codex-skills.sh`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/install-codex-skills.sh), then invoke skills via the `ai-berkshire` CLI using slash commands like `/investment-research` or `/financial-data`. Each skill is defined in the `skills/` directory as a Markdown file that specifies exact workflows and data requirements.

### What is the difference between the `skills/` and `codex-skills/` directories?

The `skills/` directory contains the **canonical source definitions** written in plain Markdown. The `codex-skills/` directory contains **generated Codex-compatible packages** created by [`scripts/sync-codex-skills.py`](https://github.com/xbtlin/ai-berkshire/blob/main/scripts/sync-codex-skills.py). This dual structure ensures that both human readers and automated Codex agents use identical skill definitions.

### How does AI Berkshire ensure data accuracy across its skills?

Every skill adheres to the **Financial Data Discipline** mandated in [`skills/financial-data.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/financial-data.md). This requires dual-source verification (e.g., Macrotrends + StockAnalysis for US equities) and uses [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) to perform exact-arithmetic calculations, preventing the approximation errors common in LLM "mental math."

### Can I combine multiple AI Berkshire skills in a single workflow?

Yes. The I-6 skills are designed to be **composable**. For example, running `/investment-research` automatically chains `/financial-data` and `/earnings-review` to gather and validate data before generating the final report. This orchestration ensures that validation rules propagate through multi-step research tasks.