Datapack Builder
AnthropicOfficialPublished by Anthropic
- Skill
- Content generator
- Business and productivity
- Apache-2.0
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The datapack-builder skill provides a rigorous, step-by-step procedure for transforming raw financial information from sources like SEC filings, CIMs, and web data into standardized, professional Excel workbooks. Designed for private equity and M&A due diligence, it enforces strict formatting, formula-based calculations, and clear documentation of assumptions to ensure data integrity and auditability for investment committee review.
What it does
- Extracts and normalizes financial data from diverse source documents and web inputs.
- Standardizes financial reporting into a consistent 8-tab Excel workbook structure.
- Enforces strict formatting rules for currency, operational metrics, and percentages.
- Requires formula-based calculations to ensure dynamic updates and auditability.
- Documents normalization adjustments and assumptions with clear source citations.
- Facilitates scenario building, including management, base, and downside cases.
When to use it
- During M&A due diligence to synthesize target company data.
- When preparing investment committee materials for private equity analysis.
- To standardize financial reporting across multiple portfolio companies.
- When transforming unstructured data from offering memorandums into structured models.
Advantages
- Ensures zero-tolerance for errors through mandatory source tracing.
- Promotes consistency across all financial models with standardized formatting.
- Eliminates hardcoded values by enforcing formula-based calculations.
- Provides a professional, audit-ready presentation for executive review.
- Reduces manual effort in normalizing disparate financial data sources.
Usage examples
- “Build a financial data pack for Company X using the attached CIM and latest SEC 10-K filing.”
- The agent will extract historical financials, normalize the data, and generate a structured Excel workbook with an executive summary, financial statements, and key operating metrics.
- “Create a base case and downside scenario for our target acquisition based on the provided management projections.”
- The agent will apply conservative adjustments to the management case, document the rationale for each change, and produce a comparative scenario analysis in the workbook.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/anthropics/datapack-builder/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip datapack-builder.zip -d .agents/skills
Documentation by Anthropic
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 Negatives: $(123.0) NOT -$123
RULE 2: Operational data (counting things) → Number format, NO $ Triggers: Units, Stores, Locations, Employees, Customers, Square Feet, Properties, Headcount Format: #,##0 with commas Negatives: (123) consistent with rest of table
RULE 3: Percentages (rates and ratios) → Percentage format Triggers: Margin, Growth, Rate, Percentage, Yield, Return, Utilization, Occupancy Format: 0.0% for one decimal place Display: 15.0% NOT 0.15
RULE 4: Years → Text format to prevent comma insertion Format: Text or custom to prevent 2,024 Display: 2020, 2021, 2022, 2023A, 2024E
RULE 5: When context is mixed, each metric gets its own appropriate format Example:
Segment Analysis, 2022, 2023, 2024
Retail Revenue, $50.0, $55.0, $60.0
Stores, 100, 110, 120
Revenue per Store, $0.5, $0.5, $0.5Revenue and per-store metrics use $, Store count uses number format.
RULE 6: Use formulas for all calculations → Never hardcode calculated values All subtotals, totals, ratios, and derived metrics must be formula-based, not hardcoded values. This ensures accuracy and allows for dynamic updates.
3. Professional Presentation Standards
Formatting Standards:
Color Scheme - Two Layers:
Layer 1: Font Colors (MANDATORY from xlsx skill)
Blue text (RGB: 0,0,255): ALL hardcoded inputs (historical data, assumptions), NOT normal text
Black text (RGB: 0,0,0): ALL formulas and calculations
Green text (RGB: 0,128,0): Links to other sheets
Layer 2: Fill Colors (Optional for enhanced presentation)
Fill colors are optional and should only be applied if requested by the user or if enhancing presentation
If the user requests colors or professional formatting, use this standard scheme:
Section headers: Dark blue (RGB: 68,114,196) background with white text
Sub-headers/column headers: Light blue (RGB: 217,225,242) background with black text
Input cells: Light green/cream (RGB: 226,239,218) background with blue text
Calculated cells: White background with black text
Users can override with custom brand colors if specified
How the layers work together (if fill colors are used):
Input cell: Blue text + light green fill = "User-entered data"
Formula cell: Black text + white background = "Calculated value"
Sheet link: Green text + white background = "Reference from another tab"
Font color tells you WHAT it is. Fill color tells you WHERE it is (if used).
IMPORTANT: Font colors from xlsx skill are mandatory. Fill colors are optional - default is white/no fill unless the user requests enhanced formatting or colors.
Always apply:
Bold headers, left-aligned
Numbers right-aligned
2-space indentation for sub-items
Single underline above subtotals
Double underline below final totals
Freeze panes on row/column headers
Minimal borders (only where structurally needed)
Consistent font (typically Calibri or Arial 11pt)
Never include:
Borders around every cell
Multiple fonts or font sizes
Charts unless specifically requested
Excessive formatting or decoration
Structural Consistency
Use the standard 8-tab structure unless explicitly instructed otherwise:
Executive Summary
Historical Financials (Income Statement)
Balance Sheet
Cash Flow Statement
Operating Metrics
Property/Segment Performance (if applicable)
Market Analysis
Investment Highlights
Tab 1: Executive Summary
Purpose: One-page overview for busy executives
Contents:
Company overview (2-3 sentences on business model)
Key investment highlights (3-5 bullet points)
Financial snapshot table (Revenue, EBITDA, Growth for last 3 years + projections)
Transaction overview if applicable
Key metrics prominently displayed
Format: Clean, bold headers, minimal decoration, critical numbers emphasized
Tab 2: Historical Financials (Income Statement)
Purpose: Complete profit and loss history
Contents:
Revenue breakdown by segment/product line
Cost of goods sold / Cost of revenue
Gross profit and gross margin %
Operating expenses detailed (S&M, R&D, G&A)
EBITDA and Adjusted EBITDA
Below-the-line items (D&A, interest, taxes)
Net income
Format:
Years as columns (text format: 2020, 2021, 2022)
$ millions or $ thousands (specify units clearly at top)
Accounting format for all financial data
Single underline above subtotals, double underline below net income
Right-align all numbers
Tab 3: Balance Sheet
Purpose: Financial position at period end
Contents:
Current assets (cash, AR, inventory, prepaid, other)
Long-term assets (PP&E, intangibles, goodwill, other)
Current liabilities (AP, accrued expenses, current portion of debt, other)
Long-term liabilities (long-term debt, deferred taxes, other)
Shareholders' equity (common stock, retained earnings, other)
Format:
Verify formula: Assets = Liabilities + Equity
Consistent date labeling
Include working capital calculation
Single underline above major subtotals, double underline for final totals
Tab 4: Cash Flow Statement
Purpose: Cash generation and use analysis
Contents:
Operating cash flow (indirect method preferred)
Investing cash flow (capex, acquisitions, asset sales)
Financing cash flow (debt issuance/repayment, equity, dividends)
Net change in cash
Beginning and ending cash balances
Format:
Link to income statement and balance sheet where possible
Show reconciliation of net income to operating cash flow
Clear labeling of cash uses (outflows) vs sources (inflows)
Tab 5: Operating Metrics
Purpose: Non-financial KPIs and operational data
Contents (industry-dependent):
Unit volumes, customer counts, locations
Productivity metrics (revenue per employee, per store, per unit)
Capacity utilization
Market share
Customer retention/churn rates
Industry-specific KPIs
CRITICAL FORMAT NOTE: NO dollar signs on operational metrics. These are quantities, not currency.
Format:
Clear units specified (customers, employees, stores, square feet, etc.)
Whole numbers with commas: 1,250 NOT $1,250
Percentages for rates: 95.0%
Right-align numbers
Tab 6: Property/Segment Performance (if applicable)
Purpose: Detailed breakdown by business unit, property, or segment
Contents:
Revenue and profitability by segment
Key metrics by location/product
Segment-specific KPIs
Comparative performance analysis
Format: Consistent with financial tabs for revenue/EBITDA, number format for operational metrics
Tab 7: Market Analysis
Purpose: Industry context and competitive positioning
Contents:
Market size and growth trends
Competitive landscape overview
Market share analysis
Industry benchmarks and peer comparisons
Regulatory environment if relevant
Format: Mix of narrative text and tables, cite sources for market data
Tab 8: Investment Highlights
Purpose: Narrative summary of key investment thesis points
Contents:
Detailed writeup of competitive strengths
Growth opportunities and strategic initiatives
Risk factors and mitigation strategies
Management assessment and track record
Investment thesis summary
Format: Clear headers, bullet points, concise paragraphs
STEP-BY-STEP WORKFLOW
Phase 1: Document Processing and Data Extraction
Step 1.1: Analyze source data
Access source materials: uploaded documents, web search for public filings, or MCP server data
Review data structure and identify key sections
Locate financial statements (typically 3-5 years historical)
Identify management projections if included
Note fiscal year end date
Flag any data quality issues immediately
Step 1.2: Extract financial statements
Locate historical income statement data
Extract balance sheet snapshots (year-end or quarter-end)
Find cash flow statement
Extract management projections if available
Note all page references for traceability
Step 1.3: Extract operating metrics
Identify non-financial KPIs relevant to industry
Capture unit economics data
Extract customer/location/capacity data
Document growth metrics and trends
Step 1.4: Extract market and industry data
Competitive positioning information
Market size and growth rates
Industry benchmark data
Peer comparison information
Step 1.5: Note key context
Transaction structure and rationale
Management team background
Investment highlights from source materials
Risk factors and considerations
Any data gaps or inconsistencies
Phase 2: Data Normalization and Standardization
Step 2.1: Normalize accounting presentation
Ensure consistent line item names across all years
Standardize revenue recognition treatment
Identify and document one-time charges
Create "Adjusted EBITDA" reconciliation if needed
Note any accounting policy changes
Step 2.2: Apply format detection logic For each data point, determine format based on full context:
Read tab name, table title, column header, and row label
Apply essential rules (see above)
When uncertain, examine original source document
Default to cleaner formatting (less is more)
Step 2.3: Identify normalization adjustments Common adjustments to document:
Restructuring charges (add back if truly non-recurring)
Stock-based compensation (add back per industry standard)
Acquisition-related costs (add back, specify amounts)
Legal settlements or litigation costs (evaluate recurrence risk)
Asset sales or impairments (exclude from operating results)
Related party adjustments (normalize to market rates) Note: Source citation format varies by data source (page numbers for documents, URLs for web sources, server references for MCP data)
Step 2.4: Create adjustment schedule For every normalization:
Document what was adjusted and why
Cite source (document page number, URL, or data source reference)
Quantify dollar impact by year
Assess recurrence risk
Show calculation from reported to adjusted figures
Step 2.5: Verify data integrity
Confirm subtotals sum correctly using formulas
Verify balance sheet balances
Check cash flow ties to balance sheet changes
Cross-check numbers across tabs for consistency
Flag any discrepancies for investigation
Phase 3: Build Excel Workbook
CRITICAL: Use xlsx skill for all Excel file manipulation. Read xlsx skill documentation before proceeding.
Step 3.1: Create standardized tab structure Create workbook with tabs:
Executive Summary
Historical Financials
Balance Sheet
Cash Flow
Operating Metrics
Property Performance (if applicable)
Market Analysis
Investment Highlights
Step 3.2: Build each tab with proper formatting Apply formatting rules systematically:
Headers: Bold, left-aligned, 11pt font
Financial data: Currency format $#,##0.0 for millions
Operational data: Number format #,##0 (no $)
Percentages: 0.0% format
Years: Text format to prevent comma insertion
Negatives: Use accounting format with parentheses
Underlines: Single above subtotals, double below totals
Step 3.3: Insert formulas for calculations
All subtotals and totals must be formula-based
Link balance sheet to income statement where appropriate
Link cash flow to both income statement and balance sheet
Create cross-tab references for validation
Avoid hardcoding any calculated values
<correct_patterns>
Row Reference Tracking - Copy This Pattern
Store row numbers when writing data, then reference them in formulas:
# ✅ CORRECT - Track row numbers as you write
revenue_row = row
write_data_row(ws, row, "Revenue", revenue_values)
row += 1
ebitda_row = row
write_data_row(ws, row, "EBITDA", ebitda_values)
row += 1
# Use stored row numbers in formulas
margin_row = row
for col in year_columns:
cell = ws.cell(row=margin_row, column=col)
cell.value = f"={get_column_letter(col)}{ebitda_row}/{get_column_letter(col)}{revenue_row}"For complex models, use a dictionary:
row_refs = {
'revenue': 5,
'cogs': 6,
'gross_profit': 7,
'ebitda': 12
}
# Later in formulas
margin_formula = f"=B{row_refs['ebitda']}/B{row_refs['revenue']}"</correct_patterns>
<common_mistakes>
WRONG: Hardcoded Row Offsets
Don't use relative offsets - they break when table structure changes:
# ❌ WRONG - Fragile offset-based references
formula = f"=B{row-15}/B{row-19}" # What is row-15? What is row-19?
# ❌ WRONG - Magic numbers
formula = f"=B{current_row-10}*C{current_row-20}"Why this fails:
Breaks silently when you add/remove rows
Impossible to verify correctness by reading code
Creates debugging nightmares in the delivered Excel file
</common_mistakes>
Step 3.4: Apply professional presentation
Freeze top row and first column on each data tab
Set appropriate column widths (typically 12-15 characters)
Right-align all numeric data
Left-align all text and headers
Add single/double underlines per accounting standards
Ensure clean, minimal appearance
Phase 4: Scenario Building (if projections included)
Management Case: Present company's projections as provided in source materials:
Extract all management assumptions
Document growth rates, margin expansion, capital requirements
Note key drivers and sensitivities
Flag any "hockey stick" inflections that require skepticism
Present as "Management Case" with clear labeling
Base Case (Risk-Adjusted): Apply conservative adjustments to management projections based on company-specific risk factors:
Apply revenue growth haircut reflecting execution risk and historical forecast accuracy
Moderate margin expansion assumptions based on industry benchmarks and operating leverage
Increase capex assumptions if growth-dependent
Add working capital requirements if understated
Delay synergy realization if applicable, based on integration complexity
Document all adjustments with rationale and supporting analysis
Downside Case (optional but recommended for LBO analysis): Stress test scenario based on industry cyclicality and company vulnerabilities:
Model revenue decline reflecting recession risk or competitive pressure
Assume margin compression under stress (volume deleverage, pricing pressure)
Test covenant compliance and liquidity
Assess downside protection
Document key risks being stress-tested
Documentation requirements for scenarios: Create assumptions schedule showing:
Key assumptions by scenario (revenue growth, margins, capex %)
Rationale for each adjustment
Sensitivity analysis on key variables
Historical forecast accuracy if available
Comparison to industry benchmarks
Phase 5: Quality Control and Validation
Step 5.1: Data accuracy checks Validate:
Every number traces to source (check spot samples, cite documents/URLs/servers)
All calculations are formula-based (no hardcoded values)
Subtotals and totals are mathematically correct
Years display without commas (2024 NOT 2,024)
No formula errors: #REF!, #VALUE!, #DIV/0!, #N/A
Step 5.2: Format consistency checks Verify:
Financial data has $ signs in format
Operational data has NO $ signs
Percentages display as % (15.0% not 0.15)
Negative numbers use parentheses for financial data
Headers are bold and left-aligned
Numbers are right-aligned
Years are text format
Step 5.3: Structure and completeness checks Confirm:
All required tabs present and properly sequenced
Executive summary is concise (fits on one page)
All key metrics captured comprehensively
Logical flow from summary to detail
Appropriate level of granularity in each tab
No missing data or incomplete sections
Step 5.4: Professional presentation checks Review:
Minimal borders (only for structure)
Consistent indentation (2 spaces for sub-items)
Proper accounting underlines (single and double)
Clean, professional appearance throughout
Appropriate column widths (not too narrow or wide)
Step 5.5: Documentation and assumptions checks Ensure:
All normalization adjustments documented with rationale
Source citations included (document page numbers, URLs, or data source references)
Assumptions clearly stated and reasonable
Executive summary accurate and impactful
Filename includes company name and date
Phase 6: Final Delivery
Step 6.1: Create executive summary Write concise, impactful summary including:
Company overview: business model, products/services, geography (2-3 sentences)
Key financial metrics: Revenue, EBITDA, Growth rates (table format)
Investment highlights: 3-5 key strengths or opportunities
Notable risks or considerations (briefly)
Transaction context if applicable
Step 6.2: Final file preparation
Save workbook with proper naming: CompanyName_DataPack_YYYY-MM-DD.xlsx
NORMALIZATION PATTERNS
Common Adjustments to EBITDA
1. Restructuring charges
Add back if truly non-recurring (facility closure, one-time severance)
Do NOT add back if company restructures every year
Document specific nature and rationale for non-recurrence
Example: "2023 restructuring: $3.0M facility closure, documented in source materials, one-time event"
2. Stock-based compensation
Industry standard: add back for private equity analysis
Treat as non-cash operating expense
Be consistent across all periods
Note if unusually high or includes one-time grants
3. Acquisition-related costs
Add back transaction fees, integration costs
Document specific amounts by type
Do not add back ongoing integration investments
Cite source for each adjustment
4. Legal settlements and litigation
Add back if truly isolated incident
Assess recurrence risk (one settlement vs pattern of litigation)
Document nature of settlement
Consider if this is normal course of business
5. Asset sales or impairments
Exclude gains/losses on asset sales from operating EBITDA
Remove impairment charges if truly non-recurring
Document what assets were sold/impaired and why
Adjust revenue if assets generated operating income
6. Related party adjustments
Normalize above-market related party expenses (rent, management fees)
Adjust to market rates with supporting documentation
Remove personal expenses run through business
Document market rate comparison
Conservative vs Aggressive Normalization
Management Case:
Include all adjustments management proposes
Accept company's definition of "non-recurring"
More aggressive EBITDA adjustments
Use for understanding management's view
Base Case (Recommended for investment decisions):
Only clearly non-recurring items
Apply higher scrutiny to recurring "one-time" charges
Exclude speculative adjustments
More conservative, defensible to investment committee
INDUSTRY-SPECIFIC ADAPTATIONS
Technology/SaaS
Key metrics to capture:
ARR (Annual Recurring Revenue) and MRR
Customer count by cohort
CAC (Customer Acquisition Cost) and LTV (Lifetime Value)
Churn rate (gross and net)
Net revenue retention
Rule of 40 (Growth % + EBITDA Margin %)
Magic number (sales efficiency)
Format notes: ARR is currency ($), customer count is number (no $), rates are %
Manufacturing/Industrial
Key metrics to capture:
Production capacity and capacity utilization %
Units produced by product line
Inventory turns
Gross margin by product line
Order backlog
Format notes: Units, capacity are numbers (no $), utilization is %, revenue/costs are currency
Real Estate/Hospitality
Key metrics to capture:
Properties/rooms/square footage
Occupancy rates %
ADR (Average Daily Rate) - currency format
RevPAR (Revenue per Available Room) - currency format
NOI (Net Operating Income) - currency format
Cap rates %
FF&E reserve
Format notes: Rooms/sqft are numbers, occupancy is %, ADR/RevPAR are currency
Healthcare/Services
Key metrics to capture:
Locations/facilities
Providers/employees
Patients/visits (volume metrics)
Revenue per visit - currency
Payor mix %
Same-store growth %
Format notes: Locations/visits are numbers, revenue per visit is currency, rates are %
FINAL DELIVERY CHECKLIST
Complete this checklist before delivering the data pack:
Structure:
All required tabs present and in logical sequence
Each tab has clear header and title
Executive summary is concise (fits on one page)
Data Accuracy:
All numbers trace to source (documents, URLs, or data servers)
Source references documented for key figures (page numbers, URLs, etc.)
All calculations are formula-based (no hardcoded calculated values)
Subtotals and totals verified
Balance sheet balances (Assets = Liabilities + Equity)
No #REF!, #VALUE!, or #DIV/0! errors
Formatting - Years and Numbers:
Years display correctly: 2020, 2021, 2022 (no commas)
Financial data has $ signs: $50.0, $125.5
Operational metrics have NO $ signs: 100 stores, 250 employees
Percentages formatted correctly: 15.0%, 25.5%
Negatives in parentheses: $(15.0) not -$15.0
Formatting - Professional Standards:
Headers bold and left-aligned
Numbers right-aligned
Consistent indentation (2 spaces for sub-items)
Single underline above subtotals
Double underline below final totals
Frozen panes on headers
Consistent font throughout
Minimal borders (only for structure)
Clean, professional appearance throughout
Content Completeness:
Financial statements complete (IS, BS, CF)
Operating metrics comprehensively captured
Normalization adjustments documented
Assumptions clearly stated
Executive summary clear, concise, and impactful
Investment highlights compelling
Market analysis provides context
Documentation:
All normalization adjustments explained
Every data cell cited from source with comments and links (document page numbers, URLs, or data source references)
Assumptions documented with rationale
Any data limitations noted
Filename follows convention: CompanyName_DataPack_YYYY-MM-DD.xlsx
Final Output:
File saved to outputs with proper naming convention
All quality control checks passed
Files
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Requirements and compatibility
Written for: Claude Code, Claude apps
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an MCP server, Needs Python
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Anthropic
- Publisher
- Anthropic (Official)
- Source
- anthropics/financial-services · plugins/vertical-plugins/investment-banking/skills/datapack-builder · commit 6056506
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Anthropic or Anthropic.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download datapack-builder.zip