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datapack-builder

Constructs standardized financial Excel workbooks from CIMs, SEC filings, and web search data using Python scripts and xlsx skill.

26|2|Updated Apr 30, 2026
Search Tags:#investment#financial data#Excel#financial analysis#data normalization
One-click install
npx skills add https://github.com/ViviennaMAO/money_banking_financial_market --skill datapack-builder-viviennamao
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datapack-builder
Source: https://github.com/ViviennaMAO/money_banking_financial_market/tree/main/financial-services-main/plugins/vertical-plugins/investment-banking/skills/datapack-builder
Command: npx skills add https://github.com/ViviennaMAO/money_banking_financial_market --skill datapack-builder-viviennamao

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, xlsx, requests, and includes scripts (resource) and assets (resource) components.

What problem does it solve?

This Skill addresses the complex task of building standardized financial data packs, making it easier to analyze and present financial data for investment decision-making.

Core Features & Use Cases

  • Data Extraction and Normalization: Extract financial and operational data from various sources, including CIMs, offering memorandums, SEC filings, and web search.
  • Standardization: Normalize and standardize financial data into consistent, investment committee-ready Excel workbooks.
  • Use Case: Utilize this Skill to process data from a company's SEC filings and create a comprehensive financial data pack with standardized formatting and presentation.

Quick Start

Run the datapack-builder skill with the command: datapack-builder extract data_from_sec_filings.pdf --output data_pack.xlsx

Frequently Asked Questions about datapack-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract financial data from SEC filings and CIMs for investment analysis?▼

Standardize financial data from diverse sources by normalizing extracted figures into consistent formats, producing investment committee-ready Excel workbooks suitable for comprehensive financial analysis and presentation.

Can I normalize financial data from offering memorandums into Excel workbooks automatically?▼

Yes, you can normalize financial data from offering memorandums into Excel workbooks by running Python data processing scripts that extract, standardize, and format the diverse data into a structured data pack using pandas and numpy.

Does this financial data normalization approach require Python and pandas to build data packs?▼

Yes, building standardized financial data packs requires Python, pandas, numpy, and the xlsx skill, because Python scripts handle the data extraction and normalization while xlsx generates the final Excel workbook output.

What is the best way to standardize financial data from diverse sources for an investment committee?▼

The best way to standardize financial data for an investment committee is to consolidate information from SEC filings, web searches, and CIMs into normalized Excel workbooks, ensuring consistent formatting for investment decision-making.

How do I create a standardized financial data pack from diverse sources step by step?▼

Create a standardized financial data pack by running the datapack-builder command on your source files, which extracts the financial figures, normalizes them, and outputs a formatted Excel workbook for investment analysis.

What types of financial documents can I use to build a standardized investment data pack?▼

You can build a standardized investment data pack from Confidential Information Memorandums (CIMs), offering memorandums, SEC filings, and web search results, extracting and standardizing the financial data into Excel workbooks.

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