datapack-builder
Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Extract, normalize, and standardize financial data into investment committee-ready Excel workbooks with consistent structure, proper formatting, and documented assumptions. Use for M&A due diligence, private equity analysis, investment committee materials, and standardizing financial reporting across portfolio companies. Do not use for simple financial calculations or working with already-completed data packs.
Best for M&A due diligenceWorks with GitHubHigh risk
⌘source
- author
@anthropics- language
- Python
★11kstars
1.5kforks
May 6, 2026
✦overview.md
Key Features
- ·Extract data from CIMs, SEC filings, web search, MCP servers
- ·Normalize and standardize financial data
- ·Produce investment committee-ready Excel workbooks
- ·Ensures data accuracy with traceability and formulas
Use Cases
- →Building a financial data pack from a CIM during M&A due diligence
- →Creating standardized reporting packages for portfolio companies
- →Preparing investment committee materials from SEC filings
Best for
- ✓M&A due diligence
- ✓private equity analysis
- ✓investment committee materials
Not ideal for
- !simple financial calculations
- !working with already-completed data packs
FAQs
name
datapack-builder
description
Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Extract, normalize, and standardize financial data into investment committee-ready Excel workbooks with consistent structure, proper formatting, and documented assumptions. Use for M&A due diligence, private equity analysis, investment committee materials, and standardizing financial reporting across portfolio companies. Do not use for simple financial calculations or working with already-completed data packs.
Financial Data Pack Builder
Build professional, standardized financial data packs for private equity, investment banking, and asset management. Transform financial data from CIMs, offering memorandums, SEC filings, web search, or MCP server access into polished Excel workbooks ready for investment committee review.
Important: Use the xlsx skill for all Excel file creation and manipulation throughout this workflow.
CRITICAL SUCCESS FACTORS
Every data pack must achieve these standards. Failure on any point makes the deliverable unusable.
1. Data Accuracy (Zero Tolerance for Errors)
- Trace every number to source document with page reference
- Use formula-based calculations exclusively (no hardcoded values)
- Cross-check subtotals and totals for internal consistency
- Verify balance sheet balances: Assets = Liabilities + Equity
- Confirm cash flow ties to balance sheet changes
2. ESSENTIAL RULES
RULE 1: Financial data (measuring money) → Currency format with $ Triggers: Revenue, Sales, Income, EBITDA, Profit, Loss, Cost, Expense, Cash, Debt, Assets, Liabilities, Equity, Capex Format: $#,##0.0 for millions, $#,##0 for thousands
$install
1-click copynpx skills add anthropics/financial-services --skill datapack-builderSafety assessment
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5/ 5
excellentVery clear and well structured, with almost no room for misunderstanding.
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5/ 5
very highHighly actionable with clear, concrete steps that an agent can follow directly.