# Where to Find Financial Rigor Analysis Tool Files in AI-Berkshire

> Find financial rigor analysis tool files within the xbtlin/ai-berkshire repository. Discover the core logic in tools/financial_rigor.py and streamline your financial analysis.

- Repository: [Xbt Lin/ai-berkshire](https://github.com/xbtlin/ai-berkshire)
- Tags: how-to-guide
- Published: 2026-06-28

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**The financial rigor analysis tool files are located in the `tools/` directory at the root of the `xbtlin/ai-berkshire` repository, with the core logic implemented in [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py).**

The `xbtlin/ai-berkshire` repository provides a comprehensive toolkit for rigorous financial analysis and valuation verification. All utility scripts for implementing **financial rigor analysis** are centralized in the `tools/` directory, making them easily discoverable and importable across the project's skill workflows and report generation pipelines.

## Location of Financial Rigor Analysis Tools

### Primary Module: financial_rigor.py

The core implementation for **financial rigor analysis** is located at [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) in the repository root. This module contains functions for cross-source valuation verification, exact-arithmetic calculations, and consistency enforcement. According to the source code structure, this file sits alongside other specialized utilities in the `tools/` folder, following a clear separation of concerns that keeps validation logic modular and reusable.

### Supporting Audit and Data Utilities

Several companion files in the same `tools/` directory extend the financial rigor capabilities:

- **[`tools/report_audit.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/report_audit.py)** – Provides generic audit utilities for generated research reports, including structure and citation validation.
- **[`tools/morningstar_fair_value.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/morningstar_fair_value.py)** – Handles fetching and processing of fair-value data from Morningstar for valuation comparisons.
- **[`tools/stock_screener.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/stock_screener.py)** – Contains stock-screening utilities used by various analysis pipelines throughout the project.
- **[`tools/xueqiu_scraper.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/xueqiu_scraper.py)** – Implements scraping functionality for Xueqiu data used in valuation pipelines.
- **[`tools/ashare_data.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/ashare_data.py)** – Manages specialized functions for handling Chinese A-share market data.

## Key Functions and Capabilities

The [`financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/financial_rigor.py) module exposes several critical functions for ensuring data integrity throughout the analysis pipeline.

**Cross-Source Valuation Verification**

The `compare_valuations()` function enables rigorous comparison between multiple data sources, such as Morningstar and Xueqiu datasets. This function ensures market capitalization figures and other valuation metrics align across independent sources before final analysis.

**Exact-Arithmetic Calculations**

The module implements precise arithmetic utilities to avoid floating-point errors common in financial calculations. This ensures that valuation comparisons maintain mathematical rigor and consistency.

**Report Validation**

Through integration with [`tools/report_audit.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/report_audit.py), the `validate_market_caps()` function checks generated reports for consistency with verified source data. This catches discrepancies between cited market values and calculated figures.

## Implementation Examples

### Cross-Source Valuation Comparison

Import the primary validation function to compare DataFrames from different financial data sources:

```python
from tools.financial_rigor import compare_valuations

# Assume DataFrames from different sources with a ticker column

df_source_a = ...  # e.g., scraped from Morningstar

df_source_b = ...  # e.g., scraped from Xueqiu

# Perform rigorous cross-source comparison

discrepancies = compare_valuations(df_source_a, df_source_b, key="ticker")
print(discrepancies.head())

```

### Comprehensive Report Auditing

Combine the audit and validation tools to verify generated reports:

```python
from tools.report_audit import audit_report
from tools.financial_rigor import validate_market_caps

report_path = "reports/annual_brazilian_pe_analysis.md"

# Run the generic report audit for structure and citations

audit_issues = audit_report(report_path)

# Validate specific market-cap figures used in the report

validation_issues = validate_market_caps(report_path)

# Combine results for review

all_issues = audit_issues + validation_issues
for issue in all_issues:
    print(issue)

```

## Integration with Data Pipeline Tools

The financial rigor tools integrate seamlessly with data acquisition modules located in the same `tools/` directory. The [`tools/morningstar_fair_value.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/morningstar_fair_value.py) and [`tools/xueqiu_scraper.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/xueqiu_scraper.py) files feed raw data into the validation functions, while [`tools/ashare_data.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/ashare_data.py) provides specialized handling for Chinese equity markets. This architecture ensures that **financial rigor analysis** occurs at both the ingestion and reporting stages of the data pipeline, maintaining data integrity from source to final output.

## Summary

- The primary **financial rigor analysis** tools are located in [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) within the `xbtlin/ai-berkshire` repository.
- Key functions include `compare_valuations()` for cross-source verification and `validate_market_caps()` for report auditing against source data.
- Supporting utilities in [`tools/report_audit.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/report_audit.py), [`tools/morningstar_fair_value.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/morningstar_fair_value.py), and [`tools/xueqiu_scraper.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/xueqiu_scraper.py) provide a complete validation ecosystem.
- All tool files reside in the `tools/` directory at the repository root, following a modular structure that enables easy import and reuse across different analysis skills.

## Frequently Asked Questions

### What is the main file for financial rigor analysis in AI-Berkshire?

The main file is [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py), which contains the core validation functions including `compare_valuations()` and `validate_market_caps()` for cross-source verification and exact-arithmetic calculations.

### How do I import the financial rigor functions into my script?

You can import directly from the tools module using `from tools.financial_rigor import compare_valuations, validate_market_caps`. Ensure your script runs from the repository root or that the `tools/` directory is in your Python path to resolve the imports correctly.

### What other tool files support financial rigor analysis?

The ecosystem includes [`tools/report_audit.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/report_audit.py) for general report auditing, [`tools/morningstar_fair_value.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/morningstar_fair_value.py) and [`tools/xueqiu_scraper.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/xueqiu_scraper.py) for data acquisition, [`tools/stock_screener.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/stock_screener.py) for filtering equities, and [`tools/ashare_data.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/ashare_data.py) for Chinese market data handling. These files work together to provide comprehensive validation capabilities.

### Where exactly are these tool files located in the repository structure?

All tool files are located in the `tools/` directory at the root of the `xbtlin/ai-berkshire` repository, following the path pattern `tools/<module_name>.py`. The primary file for financial rigor can be accessed at [`tools/financial_rigor.py`](https://github.com/xbtlin/ai-berkshire/blob/main/tools/financial_rigor.py) or via the raw URL at `https://raw.githubusercontent.com/xbtlin/ai-berkshire/main/tools/financial_rigor.py`.