# How AI Berkshire Tracks Investment Theses with the /thesis-tracker Skill

> Discover how AI Berkshire tracks investment theses with the /thesis-tracker skill. Learn about its post-buy discipline, structured markdown reports, and quarterly re-evaluation for improved Thesis Health Scores.

- Repository: [Xbt Lin/ai-berkshire](https://github.com/xbtlin/ai-berkshire)
- Tags: how-to-guide
- Published: 2026-07-29

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**The `/thesis-tracker` skill implements a post-buy discipline system that continuously monitors investment theses by creating structured markdown reports and re-evaluating core assumptions quarterly to generate a numerical Thesis Health Score.**

The `xbtlin/ai-berkshire` repository provides an AI-powered investment analysis framework that transforms static investment ideas into living documents requiring rigorous validation. At the center of this methodology sits the `/thesis-tracker` skill, which automates the creation and monitoring of investment theses through a dual-mode workflow defined in [`skills/thesis-tracker.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/thesis-tracker.md).

## The Two-Mode Workflow Architecture

The skill operates in two distinct modes depending on whether a thesis file already exists for the target company.

### Mode A: Establishing a New Investment Thesis

When initiating coverage on a new position, the skill creates a comprehensive thesis document at `reports/{Company}-thesis.md`. This process begins by gathering current market data and validating valuation metrics through [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py).

The generated markdown report contains four critical sections:

- **Five-Sentence Investment Thesis** – Answering key investment questions in exactly five sentences, establishing the core bullish case【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L44-L53】
- **Core Assumption List** – Enumerating testable hypotheses with verification methods and monitoring frequencies【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L61-L68】
- **Red-Line List** – Deal-breaker conditions that trigger immediate re-evaluation or exit【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L71-L78】
- **Valuation Anchors** – Current price, PE ratio, market cap, intrinsic value estimate, and safety margin calculations【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L85-L91】

### Mode B: Tracking Existing Theses

When a thesis file exists, the skill enters monitoring mode, executing a seven-step re-evaluation workflow:

1. **Load Historical Data** – Retrieves the stored thesis, assumptions, red-lines, and previous check records【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L8-L14】
2. **Fetch Live Data** – Retrieves latest earnings, news, price movements, and insider-trading data via **WebSearch**【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L18-L22】
3. **Assumption Validation** – Re-evaluates each core assumption, updating status indicators in a tracking table【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L24-L33】
4. **Red-Line Monitoring** – Checks every deal-breaker condition for violation【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L40-L46】
5. **Valuation Refresh** – Updates valuation anchors with current market data【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L74-L82】
6. **Health Score Calculation** – Computes the Thesis Health Score using the weighted formula【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L89-L92】
7. **Append Results** – Records the new check results to the thesis markdown file with timestamp【/cache/repos/github.com/xbtlin/ai-berkshire/main/skills/thesis-tracker.md#L94-L100】

## Thesis Health Score Calculation methodology

The **Thesis Health Score** quantifies thesis validity on a numerical scale using the following weighted formula implemented in the skill logic:

```python
health = 10 \
    - (⚫ * 3) \   # broken assumptions

    - (🔴 * 2) \   # damaged assumptions  

    - (🟡 * 1) \   # weakened assumptions

    - (red_lines * 5)

```

Status indicators follow a traffic-light system:
- 🟢 **Healthy**: Assumption remains valid
- 🟡 **Weakened**: Minor deviation requiring observation
- 🔴 **Damaged**: Significant deterioration threatening thesis
- ⚫ **Broken**: Invalidated assumption requiring thesis revision

Red-line violations incur a severe 5-point penalty each, reflecting their status as deal-breakers that typically warrant immediate position closure.

## Technical Implementation and Source Files

The thesis-tracking capability spans multiple components within the repository:

| Component | File Path | Description |
|-----------|-----------|-------------|
| **Skill Definition** | [`skills/thesis-tracker.md`](https://github.com/xbtlin/ai-berkshire/blob/main/skills/thesis-tracker.md) | Canonical workflow documentation and prompt templates |
| **Codex Adapter** | [`codex-skills/thesis-tracker/SKILL.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-skills/thesis-tracker/SKILL.md) | Generated adapter mapping markdown to callable skill |
| **Prompt Wrapper** | [`codex-prompts/thesis-tracker.md`](https://github.com/xbtlin/ai-berkshire/blob/main/codex-prompts/thesis-tracker.md) | Codex entry point prompt configuration |
| **Validation Tool** | [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) | Utility for verifying valuation calculations |
| **Output Reports** | `reports/{Company}-thesis.md` | Generated living documents containing tracking tables |

According to the `xbtlin/ai-berkshire` source code, the skill automatically invokes `WebSearch` for data retrieval and executes `python3 tools/financial_rigor.py verify-valuation` to ensure mathematical rigor in all valuation anchors.

## Practical Usage Examples

Execute the thesis-tracker via command line to either establish new coverage or update existing positions:

```bash

# Create initial thesis for a new company

ai_berkshire /thesis-tracker "Tesla 建立论文"

# Run quarterly check for an existing position  

ai_berkshire /thesis-tracker "Tesla 季度检查"

```

The skill interprets the command arguments to determine which mode to execute. When the thesis file exists, it automatically triggers Mode B (tracking); when absent, it initiates Mode A (establishment).

The structured output enables downstream automation, allowing skills such as `/thesis-drift` or `/portfolio-review` to consume the health scores and assumption statuses programmatically for broader portfolio management decisions.

## Summary

- The `/thesis-tracker` skill implements a **dual-mode workflow** that creates new theses or monitors existing ones through structured markdown documents.
- **Four core components** comprise every thesis: a five-sentence summary, testable assumptions, red-line deal breakers, and valuation anchors.
- **Assumption statuses** use emoji indicators (🟢🟡🔴⚫) to track validity, feeding into a weighted health score formula that subtracts penalties for weakened, damaged, or broken assumptions.
- **Red-line violations** automatically subtract 5 points each from the health score, reflecting their severity as thesis-invalidating events.
- The system automatically invokes **[`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py)** and **WebSearch** to ensure all valuations and market data remain current and mathematically sound.

## Frequently Asked Questions

### How does the /thesis-tracker skill determine when to create versus update a thesis?

The skill checks for the existence of a thesis file at `reports/{Company}-thesis.md`. If the file is absent, it executes **Mode A** to establish a new thesis by gathering initial data and creating the structured markdown template. If the file exists, it automatically enters **Mode B** to append a new quarterly check record to the existing document.

### What triggers a red-line violation and how does it affect the health score?

**Red-lines** represent deal-breaker conditions defined during thesis establishment, such as "CEO departure" or "core product revenue decline >20%." Each triggered red-line automatically subtracts **5 points** from the 10-point health scale, typically reducing the score to exit territory (≤3 points), which signals immediate position liquidation according to the skill's recommendation logic.

### Can the thesis-tracker integrate with other AI Berkshire skills?

Yes. The skill outputs standardized markdown tables containing health scores, assumption statuses, and valuation updates that downstream skills like `/thesis-drift` (for thesis deviation analysis) and `/portfolio-review` (for aggregate portfolio health) can parse programmatically. This modular architecture enables comprehensive portfolio management workflows where individual thesis health informs broader allocation decisions.

### Where are the thesis documents physically stored in the repository?

Thesis files reside in the `reports/` directory using the naming convention `{Company}-thesis.md`. For example, Tencent's thesis is stored at `reports/腾讯/腾讯-thesis.md`. These files function as append-only logs, with each quarterly check adding new validation tables while preserving historical assumption states and health score trends.