From investment-banking
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.
npx claudepluginhub rodaquino-omni/crowtech-healthcare-finance --plugin investment-bankingThis skill uses the workspace's default tool permissions.
Build standardized data packs for CrowTech investment banking, PE diligence, and portfolio reporting. Transform CIMs, offering memorandums, SEC filings, or MCP-sourced data into polished Excel workbooks ready for IC review.
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Build standardized data packs for CrowTech investment banking, PE diligence, and portfolio reporting. Transform CIMs, offering memorandums, SEC filings, or MCP-sourced data into polished Excel workbooks ready for IC review.
Important: Use the xlsx skill for all Excel file creation and manipulation throughout this workflow.
RULE 1: Financial data (measuring money) → Currency format with $ Triggers: Revenue, EBITDA, Cost, Cash, Debt, Assets, Liabilities, Equity, Capex Format: $#,##0.0 for millions; negatives $(123.0)
RULE 2: Operational data (counting things) → Number format, NO $ Triggers: Units, Locations, Employees, Patients, Visits, Providers Format: #,##0; negatives (123)
RULE 3: Percentages → Percentage format Triggers: Margin, Growth, Rate, Yield, Utilization, Occupancy, Payor mix Format: 0.0% — display 15.0% NOT 0.15
RULE 4: Years → Text format to prevent comma insertion Display: 2020, 2021, 2022, 2023A, 2024E
RULE 5: Mixed tables — each metric gets its own appropriate format Revenue uses $, clinic count uses number format, margin uses %.
RULE 6: Formulas for all calculations — never hardcode
Font colors (MANDATORY from xlsx skill):
Fill colors (optional):
Font color tells you WHAT it is; fill tells you WHERE it is.
Always apply: bold headers left-aligned; numbers right-aligned; 2-space indent for sub-items; single underline above subtotals, double underline below totals; freeze panes; minimal borders; Calibri/Arial 11pt.
Never: borders around every cell; multiple fonts; charts unless requested.
One-page overview: business model (2-3 sentences), 3-5 investment highlights, financial snapshot table (Revenue, EBITDA, Growth for last 3 years + projections), transaction overview.
Revenue by segment, COGS, gross profit + margin %, opex detail (S&M, R&D, G&A), EBITDA and Adjusted EBITDA, D&A, interest, taxes, net income. Years as text columns; $ millions or thousands (specify units); accounting format; single/double underlines.
Current assets (cash, AR, inventory, prepaid), long-term assets (PP&E, intangibles, goodwill), current liabilities, long-term liabilities, equity. Verify Assets = Liabilities + Equity. Include working capital.
Operating (indirect), investing (capex, acquisitions), financing (debt, equity, dividends). Link to IS and BS; reconcile NI to operating CF.
Non-financial KPIs. For healthcare services: locations, providers, patients/visits, payor mix %, same-store growth %. For healthcare AI: ARR, customers, net revenue retention, Rule of 40.
CRITICAL FORMAT NOTE: NO dollar signs on operational metrics — these are quantities, not currency. Whole numbers with commas (1,250 NOT $1,250); percentages for rates.
Revenue and profitability by segment/location; segment-specific KPIs; comparative analysis.
Market size and growth, competitive landscape, peer benchmarks, regulatory environment (for healthcare: CMS rulemaking, CON laws, value-based care trends, HIPAA/SOC 2 for AI).
Narrative writeup: competitive strengths, growth opportunities, risks and mitigation, management assessment, investment thesis.
Step 1.1: Analyze source data — review documents/filings/MCP sources, locate 3-5 years of statements, note fiscal year end, flag data quality issues.
Step 1.2: Extract financial statements — historical IS, BS snapshots, CF, management projections. Record page references.
Step 1.3: Extract operating metrics — industry KPIs, unit economics, customer/location/capacity data.
Step 1.4: Extract market and industry data — competitive positioning, market size, benchmarks, peers.
Step 1.5: Note key context — transaction structure, management background, investment highlights, risks, data gaps.
Step 2.1: Normalize accounting presentation — consistent line items across years; standardize revenue recognition; flag one-time charges; build Adjusted EBITDA reconciliation; note policy changes.
Step 2.2: Apply format detection logic — read tab/table/column/row context; apply essential rules; when uncertain, examine source; default to cleaner formatting.
Step 2.3: Identify normalization adjustments — restructuring (if truly non-recurring), SBC (add back per PE standard), acquisition costs, legal settlements (evaluate recurrence), asset sales/impairments (exclude), related-party normalization. Cite source per item.
Step 2.4: Create adjustment schedule — for each normalization: what, why, source citation, $ by year, recurrence risk, reported-to-adjusted calc.
Step 2.5: Verify data integrity — formulas tie; balance sheet balances; CF ties to BS; cross-tab consistency; flag discrepancies.
CRITICAL: Use xlsx skill for all Excel file manipulation. Read xlsx skill documentation before proceeding.
Step 3.1: Create standardized tab structure — the 8 tabs above (omit Property Performance if not applicable).
Step 3.2: Build each tab with proper formatting — apply the rules above systematically (bold left-aligned headers, currency vs. number vs. percent, year text format, parentheses for negatives, single/double underlines).
Step 3.3: Insert formulas for calculations — all subtotals and totals formula-based; link BS to IS; link CF to IS and BS; create cross-tab references; avoid hardcoding.
<correct_patterns>
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>
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:
</common_mistakes>
Step 3.4: Apply professional presentation — freeze top row and first column; column widths ~12-15; right-align numbers; left-align text; single/double underlines; minimal borders.
Management Case: present company projections as provided; document growth/margin/capex assumptions; flag hockey-stick inflections.
Base Case (Risk-Adjusted): conservative adjustments — revenue growth haircut for execution risk, moderated margin expansion, higher capex if growth-dependent, working capital additions if understated, delayed synergy realization. Document each adjustment. For healthcare services, stress reimbursement-rate assumptions and same-store growth; for value-based care revenue, stress risk-sharing outcomes.
Downside Case (recommended for LBO): stress test — revenue decline, margin compression, covenant and liquidity check, downside protection.
Documentation: assumptions schedule with key drivers by scenario, rationale, sensitivities, historical forecast accuracy, industry benchmarks.
5.1 Data accuracy: every number traces to source; formulas only; subtotals correct; years without commas; no #REF!/#VALUE!/#DIV/0!/#N/A.
5.2 Format consistency: $ on financial data; no $ on operational; % formatted; negatives in parens; headers bold/left; numbers right; years text.
5.3 Structure/completeness: all tabs present; executive summary one page; key metrics captured; logical flow; appropriate granularity.
5.4 Presentation: minimal borders; consistent indentation; proper underlines; clean look; reasonable column widths.
5.5 Documentation: normalizations documented with rationale; source citations (page, URL, server); assumptions stated; executive summary impactful; filename includes company and date.
6.1 Executive summary: business model (2-3 sentences), key metrics table, 3-5 investment highlights, notable risks, transaction context.
6.2 Final file: save as CompanyName_DataPack_YYYY-MM-DD.xlsx.
1. Restructuring charges — add back only if truly non-recurring (one-time severance, facility closure). Do not add back if company restructures annually. Document nature and rationale.
2. Stock-based compensation — industry standard: add back for PE analysis; treat as non-cash opex; be consistent across periods.
3. Acquisition-related costs — add back transaction fees and integration costs; do not add back ongoing integration investments; cite source.
4. Legal settlements and litigation — add back if isolated; assess recurrence pattern; consider normal-course-of-business risk (for healthcare: malpractice exposure and Stark/AKS settlements deserve extra scrutiny).
5. Asset sales or impairments — exclude gains/losses on sales from operating EBITDA; remove non-recurring impairments; adjust revenue if assets generated operating income.
6. Related-party adjustments — normalize above-market rent/management fees to market rates with documentation; remove personal expenses.
Management Case: all management-proposed adjustments; accept company definition of non-recurring; more aggressive; use to understand management's view.
Base Case (Recommended): only clearly non-recurring items; higher scrutiny on recurring "one-time" charges; exclude speculative adjustments; defensible to IC.
ARR/MRR, customer count by cohort, CAC/LTV, gross and net churn, net revenue retention, Rule of 40, magic number. Format notes: ARR is $, customer count is #, rates are %. For healthcare AI also capture HIPAA/SOC 2 status and any FDA pathway (De Novo, 510(k)) where relevant.
Production capacity and utilization %, units by product, inventory turns, gross margin by line, order backlog. Units and capacity are numbers; utilization is %; revenue/costs are $.
Properties/rooms/sqft, occupancy %, ADR ($), RevPAR ($), NOI ($), cap rates %, FF&E reserve.
Locations/facilities, providers/employees, patients/visits, revenue per visit ($), payor mix % (Medicare / Medicaid / commercial / self-pay), same-store growth %, value-based care exposure (% capitated / MSSP / ACO REACH / MA risk), CMS rate sensitivity, corporate-practice-of-medicine and CON exposure.
Structure: all tabs present and sequenced; each tab has title; executive summary fits one page.
Data Accuracy: all numbers trace to source; formulas only; subtotals verified; BS balances; no formula errors.
Formatting — years/numbers: 2020 (no comma); $ on financial data; NO $ on operational; % correctly formatted; negatives in parens.
Formatting — professional: bold left-aligned headers; right-aligned numbers; 2-space sub-item indent; single/double underlines; frozen panes; consistent font; minimal borders.
Content completeness: IS/BS/CF complete; operating metrics comprehensive; normalizations documented; assumptions stated; summary impactful; highlights compelling; market context included.
Documentation: every data cell cited; assumptions documented; limitations noted; filename CompanyName_DataPack_YYYY-MM-DD.xlsx.
Final output: file saved with proper naming; QC checks passed.