diff --git a/optional-skills/finance/3-statement-model/SKILL.md b/optional-skills/finance/3-statement-model/SKILL.md
new file mode 100644
index 0000000000..79718c66cd
--- /dev/null
+++ b/optional-skills/finance/3-statement-model/SKILL.md
@@ -0,0 +1,432 @@
+---
+name: 3-statement-model
+description: Build fully-integrated 3-statement models (IS, BS, CF) in Excel with working capital schedules, D&A roll-forwards, debt schedule, and the plugs that make cash and retained earnings tie. Pairs with excel-author.
+version: 1.0.0
+author: Anthropic (adapted by Nous Research)
+license: Apache-2.0
+metadata:
+  hermes:
+    tags: [finance, three-statement, income-statement, balance-sheet, cash-flow, excel, openpyxl, modeling]
+    related_skills: [excel-author, pptx-author, dcf-model, lbo-model]
+---
+
+## Environment
+
+This skill assumes **headless openpyxl** — you are producing an .xlsx file on disk.
+Follow the `excel-author` skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables.
+Recalculate before delivery: `python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx`.
+
+# 3-Statement Financial Model Template Completion
+
+Complete and populate integrated financial model templates with proper linkages between Income Statement, Balance Sheet, and Cash Flow Statement.
+
+## ⚠️ CRITICAL PRINCIPLES — Read Before Populating Any Template
+
+**Formulas over hardcodes (non-negotiable):**
+- Every projection cell, roll-forward, linkage, and subtotal MUST be an Excel formula — never a pre-computed value
+- When using Python/openpyxl: write formula strings (`ws["D15"] = "=D14*(1+Assumptions!$B$5)"`), NOT computed results (`ws["D15"] = 12500`)
+- The ONLY cells that should contain hardcoded numbers are: (1) historical actuals, (2) assumption drivers in the Assumptions tab
+- If you find yourself computing a value in Python and writing the result to a cell — STOP. Write the formula instead.
+- Why: the model must flex when scenarios toggle or assumptions change. Hardcodes break every downstream integrity check silently.
+
+**Verify step-by-step with the user:**
+1. **After mapping the template** → show the user which tabs/sections you've identified and confirm before touching any cells
+2. **After populating historicals** → show the user the historical block and confirm values/periods match source data
+3. **After building IS projections** → run the subtotal checks, show the user the projected IS, confirm before moving to BS
+4. **After building BS** → show the user the balance check (Assets = L+E) for every period, confirm before moving to CF
+5. **After building CF** → show the user the cash tie-out (CF ending cash = BS cash), confirm before finalizing
+6. **Do NOT populate the entire model end-to-end and present it complete** — break at each statement, show the work, catch errors early
+
+## Formatting — Professional Blue/Grey Palette (Default unless template/user specifies otherwise)
+
+**Keep colors minimal.** Use only blues and greys for cell fills. Do NOT introduce greens, yellows, oranges, or multiple accent colors — a clean model uses restraint.
+
+| Element | Fill | Font |
+|---|---|---|
+| Section headers (IS / BS / CF titles) | Dark blue `#1F4E79` | White bold |
+| Column headers (FY2024A, FY2025E, etc.) | Light blue `#D9E1F2` | Black bold |
+| Input cells (historicals, assumption drivers) | Light grey `#F2F2F2` or white | Blue `#0000FF` |
+| Formula cells | White | Black |
+| Cross-tab links | White | Green `#008000` |
+| Check rows / key totals | Medium blue `#BDD7EE` | Black bold |
+
+**That's 3 blues + 1 grey + white.** If the template has its own color scheme, follow the template instead.
+
+Font color signals *what* a cell is (input/formula/link). Fill color signals *where* you are (header/data/check).
+
+## Model Structure
+
+### Identifying Template Tab Organization
+
+Templates vary in their tab naming conventions and organization. Before populating, review all tabs to understand the template's structure. Below are common tab names and their typical contents:
+
+| Common Tab Names | Contents to Look For |
+|------------------|----------------------|
+| IS, P&L, Income Statement | Income Statement |
+| BS, Balance Sheet | Balance Sheet |
+| CF, CFS, Cash Flow | Cash Flow Statement |
+| WC, Working Capital | Working Capital Schedule |
+| DA, D&A, Depreciation, PP&E | Depreciation & Amortization Schedule |
+| Debt, Debt Schedule | Debt Schedule |
+| NOL, Tax, DTA | Net Operating Loss Schedule |
+| Assumptions, Inputs, Drivers | Driver assumptions and inputs |
+| Checks, Audit, Validation | Error-checking dashboard |
+
+**Template Review Checklist**
+- Identify which tabs exist in the template (not all templates include every schedule)
+- Note any template-specific tabs not listed above
+- Understand tab dependencies (e.g., which schedules feed into the main statements)
+- Locate input cells vs. formula cells on each tab
+
+### Understanding Template Structure
+
+Before populating a template, familiarize yourself with its existing layout to ensure data is entered in the correct locations and formulas remain intact.
+
+**Identifying Row Structure**
+- Locate the model title at top of each tab
+- Identify section headers and their visual separation
+- Find the units row indicating $ millions, %, x, etc.
+- Note column headers distinguishing Actuals vs. Estimates periods
+- Confirm period labels (e.g., FY2024A, FY2025E)
+- Identify input cells vs. formula cells (typically distinguished by font color)
+
+**Identifying Column Structure**
+- Confirm line item labels in leftmost column
+- Verify historical years precede projection years
+- Note the visual border separating historical from projected periods
+- Check for consistent column order across all tabs
+
+**Working with Named Ranges**
+Templates often use named ranges for key inputs and outputs. Before entering data:
+- Review existing named ranges in the template (Formulas → Name Manager in Excel)
+- Common named ranges include: Revenue growth rates, cost percentages, key outputs (Net Income, EBITDA, Total Debt, Cash), scenario selector cell
+- Ensure inputs are entered in cells that feed into these named ranges
+
+### Projection Period
+- Templates typically project 5 years forward from last historical year
+- Verify historical (A) vs. projected (E) columns are clearly separated
+- Confirm columns use fiscal year notation (e.g., FY2024A, FY2025E)
+
+## Margin Analysis
+
+**Note: The following margin analysis should only be performed if prompted by the user or if the template explicitly requires it. If no prompt is given, skip this section.**
+
+Calculate and display profitability margins on the Income Statement (IS) tab to track operational efficiency and enable peer comparison.
+
+### Core Margins to Include
+
+| Margin | Formula | What It Measures |
+|--------|---------|------------------|
+| Gross Margin | Gross Profit / Revenue | Pricing power, production efficiency |
+| EBITDA Margin | EBITDA / Revenue | Core operating profitability |
+| EBIT Margin | EBIT / Revenue | Operating profitability after D&A |
+| Net Income Margin | Net Income / Revenue | Bottom-line profitability |
+
+### Income Statement Layout with Margins
+
+Display margin percentages directly below each profit line item:
+- Gross Margin % below Gross Profit
+- EBIT Margin % below EBIT
+- EBITDA Margin % below EBITDA
+- Net Income Margin % below Net Income
+
+## Credit Metrics
+
+**Note: The following Credit analysis should only be performed if prompted by the user or if the template explicitly requires it. If no prompt is given, skip this section.**
+
+Calculate and display credit/leverage metrics on the Balance Sheet (BS) tab to assess financial health, debt capacity, and covenant compliance.
+
+### Core Credit Metrics to Include
+
+| Metric | Formula | What It Measures |
+|--------|---------|------------------|
+| Total Debt / EBITDA | Total Debt / LTM EBITDA | Leverage multiple |
+| Net Debt / EBITDA | (Total Debt - Cash) / LTM EBITDA | Leverage net of cash |
+| Interest Coverage | EBITDA / Interest Expense | Ability to service debt |
+| Debt / Total Cap | Total Debt / (Total Debt + Equity) | Capital structure |
+| Debt / Equity | Total Debt / Total Equity | Financial leverage |
+| Current Ratio | Current Assets / Current Liabilities | Short-term liquidity |
+| Quick Ratio | (Current Assets - Inventory) / Current Liabilities | Immediate liquidity |
+
+### Credit Metric Hierarchy Checks
+
+Validate that Upside shows strongest credit profile:
+- Leverage: Upside < Base < Downside (lower is better)
+- Coverage: Upside > Base > Downside (higher is better)
+- Liquidity: Upside > Base > Downside (higher is better)
+
+### Covenant Compliance Tracking
+
+If debt covenants are known, add explicit compliance checks comparing actual metrics to covenant thresholds.
+
+## Scenario Analysis (Base / Upside / Downside)
+
+Use a scenario toggle (dropdown) in the Assumptions tab with CHOOSE or INDEX/MATCH formulas.
+
+| Scenario | Description |
+|----------|-------------|
+| Base Case | Management guidance or consensus estimates |
+| Upside Case | Above-guidance growth, margin expansion |
+| Downside Case | Below-trend growth, margin compression |
+
+**Key Drivers to Sensitize**: Revenue growth, Gross margin, SG&A %, DSO/DIO/DPO, CapEx %, Interest rate, Tax rate.
+
+**Scenario Audit Checks**: Toggle switches all statements, BS balances in all scenarios, Cash ties out, Hierarchy holds (Upside > Base > Downside for NI, EBITDA, FCF, margins).
+
+## SEC Filings Data Extraction
+
+If the template specifically requires pulling data from SEC filings (10-K, 10-Q), see [references/sec-filings.md](references/sec-filings.md) for detailed extraction guidance. This reference is only needed when populating templates with public company data from regulatory filings.
+
+## Completing Model Templates
+
+This section provides general guidance for completing any 3-statement financial model template while preserving existing formulas and ensuring data integrity.
+
+### Step 1: Analyze the Template Structure
+
+Before entering any data, thoroughly review the template to understand its architecture:
+
+**Identify Input vs. Formula Cells**
+- Look for visual cues (font color, cell shading) that distinguish input cells from formula cells
+- Common conventions: Blue font = inputs, Black font = formulas, Green font = links to other sheets
+- Use Excel's Trace Precedents/Dependents (Formulas → Trace Precedents) to understand cell relationships
+- Check for named ranges that may control key inputs (Formulas → Name Manager)
+
+**Map the Template's Flow**
+- Identify which tabs feed into others (e.g., Assumptions → IS → BS → CF)
+- Note any supporting schedules and their linkages to main statements
+- Document the template's specific line items and structure before populating
+
+### Step 2: Filling in Data Without Breaking Formulas
+
+**Golden Rules for Data Entry**
+
+| Rule | Description |
+|------|-------------|
+| Only edit input cells | Never overwrite cells containing formulas unless intentionally replacing the formula |
+| Preserve cell references | When copying data, use Paste Values (Ctrl+Shift+V) to avoid overwriting formulas with source formatting |
+| Match the template's units | Verify if template uses thousands, millions, or actual values before entering data |
+| Respect sign conventions | Follow the template's existing sign convention (e.g., expenses as positive or negative) |
+| Check for circular references | If the template uses iterative calculations, ensure Enable Iterative Calculation is turned on |
+
+**Safe Data Entry Process**
+1. Identify the exact cells designated for input (usually highlighted or labeled)
+2. Enter historical data first, then verify formulas are calculating correctly for those periods
+3. Enter assumption drivers that feed forecast calculations
+4. Review calculated outputs to confirm formulas are working as intended
+5. If a formula cell must be modified, document the original formula before making changes
+
+**Handling Pre-Built Formulas**
+- If formulas reference cells you haven't populated yet, expect temporary errors (#REF!, #DIV/0!) until all inputs are complete
+- When formulas produce unexpected results, trace precedents to identify missing or incorrect inputs
+- Never delete rows/columns without checking for formula dependencies across all tabs
+
+### Step 3: Validating Formulas
+
+**Formula Integrity Checks**
+
+Before relying on template outputs, validate that formulas are functioning correctly:
+
+| Check Type | Method |
+|------------|--------|
+| Trace precedents | Select a formula cell → Formulas → Trace Precedents to verify it references correct inputs |
+| Trace dependents | Verify key inputs flow to expected output cells |
+| Evaluate formula | Use Formulas → Evaluate Formula to step through complex calculations |
+| Check for hardcodes | Projection formulas should reference assumptions, not contain hardcoded values |
+| Test with known values | Input simple test values to verify formulas produce expected results |
+| Cross-tab consistency | Ensure the same formula logic applies across all projection periods |
+
+**Common Formula Issues to Watch For**
+- Mixed absolute/relative references causing incorrect results when copied across periods
+- Broken links to external files or deleted ranges (#REF! errors)
+- Division by zero in early periods before revenue ramps (#DIV/0! errors)
+- Circular reference warnings (may be intentional for interest calculations)
+- Inconsistent formulas across projection columns (use Ctrl+\ to find differences)
+
+**Validating Cross-Tab Linkages**
+- Confirm values that appear on multiple tabs are linked (not duplicated)
+- Verify schedule totals tie to corresponding line items on main statements
+- Check that period labels align across all tabs
+
+### Step 4: Quality Checks by Sheet
+
+Perform these validation checks on each sheet after populating the template:
+
+**Income Statement (IS) Quality Checks**
+- Revenue figures match source data for historical periods
+- All expense line items sum to reported totals
+- Subtotals (Gross Profit, EBIT, EBT, Net Income) calculate correctly
+- Tax calculation logic is appropriate (handles losses correctly)
+- Forecast drivers reference assumptions tab (no hardcodes)
+- Period-over-period changes are directionally reasonable
+
+**Balance Sheet (BS) Quality Checks**
+- Assets = Liabilities + Equity for every period (primary check)
+- Cash balance matches Cash Flow Statement ending cash
+- Working capital accounts tie to supporting schedules (if applicable)
+- Retained Earnings rolls forward correctly: Prior RE + Net Income - Dividends +/- Adjustments = Ending RE
+- Debt balances tie to debt schedule (if applicable)
+- All balance sheet items have appropriate signs (assets positive, most liabilities positive)
+
+**Cash Flow Statement (CF) Quality Checks**
+- Net Income at top of CFO matches Income Statement Net Income
+- Non-cash add-backs (D&A, SBC, etc.) tie to their source schedules/statements
+- Working capital changes have correct signs (increase in asset = use of cash = negative)
+- CapEx ties to PP&E schedule or fixed asset roll-forward
+- Financing activities tie to changes in debt and equity accounts on BS
+- Ending Cash matches Balance Sheet Cash
+- Beginning Cash equals prior period Ending Cash
+
+**Supporting Schedule Quality Checks**
+- Opening balances equal prior period closing balances
+- Roll-forward logic is complete (Beginning + Additions - Deductions = Ending)
+- Schedule totals tie to main statement line items
+- Assumptions used in calculations match Assumptions tab
+
+### Step 5: Cross-Statement Integrity Checks
+
+After validating individual sheets, confirm the three statements are properly integrated:
+
+| Check | Formula | Expected Result |
+|-------|---------|-----------------|
+| Balance Sheet Balance | Assets - Liabilities - Equity | = 0 |
+| Cash Tie-Out | CF Ending Cash - BS Cash | = 0 |
+| Net Income Link | IS Net Income - CF Starting Net Income | = 0 |
+| Retained Earnings | Prior RE + NI - Dividends - BS Ending RE | = 0 (adjust for SBC/other items as needed) |
+
+### Step 6: Final Review
+
+Before considering the model complete:
+- Toggle through all scenarios (if applicable) to verify checks pass in each case
+- Review all #REF!, #DIV/0!, #VALUE!, and #NAME? errors and resolve or document
+- Confirm all input cells have been populated (search for placeholder values)
+- Verify units are consistent across all tabs
+- Save a clean version before making any additional modifications
+
+## Model Validation and Audit
+
+This section consolidates all validation checks and audit procedures for completed templates.
+
+### Core Linkages (Must Always Hold)
+
+See [references/formulas.md](references/formulas.md) for all formula details.
+
+| Check | Formula | Expected Result |
+|-------|---------|-----------------|
+| Balance Sheet Balance | Assets - Liabilities - Equity | = 0 |
+| Cash Tie-Out | CF Ending Cash - BS Cash | = 0 |
+| Cash Monthly vs Annual | Closing Cash (Monthly) - Closing Cash (Annual) | = 0 |
+| Net Income Link | IS Net Income - CF Starting Net Income | = 0 |
+| Retained Earnings | Prior RE + NI + SBC - Dividends - BS Ending RE | = 0 |
+| Equity Financing | ΔCommon Stock/APIC (BS) - Equity Issuance (CFF) | = 0 |
+| Year 0 Equity | Equity Raised (Year 0) - Beginning Equity Capital (Year 1) | = 0 |
+
+### Sign Convention Reference
+
+| Statement | Item | Sign Convention |
+|-----------|------|-----------------|
+| CFO | D&A, SBC | Positive (add-back) |
+| CFO | ΔAR (increase) | Negative (use of cash) |
+| CFO | ΔAP (increase) | Positive (source of cash) |
+| CFI | CapEx | Negative |
+| CFF | Debt issuance | Positive |
+| CFF | Debt repayments | Negative |
+| CFF | Dividends | Negative |
+
+### Circular Reference Handling
+
+Interest expense creates circularity: Interest → Net Income → Cash → Debt Balance → Interest
+
+Enable iterative calculation in Excel: File → Options → Formulas → Enable iterative calculation. Set maximum iterations to 100, maximum change to 0.001. Add a circuit breaker toggle in Assumptions tab.
+
+### Check Categories
+
+**Section 1: Currency Consistency**
+- Currency identified and documented in Assumptions
+- All tabs use consistent currency symbol and scale
+- Units row matches model currency
+
+**Section 2: Balance Sheet Integrity**
+- Assets = Liabilities + Equity (for each period)
+- Formula: Assets - Liabilities - Equity (must = 0)
+
+**Section 3: Cash Flow Integrity**
+- Cash ties to BS (CF Ending Cash = BS Cash)
+- Cash Monthly vs Annual: Closing Cash (Monthly) = Closing Cash (Annual)
+- NI ties to IS (CF Net Income = IS Net Income)
+- D&A ties to schedule
+- SBC ties to IS
+- ΔAR, ΔInventory, ΔAP tie to WC schedule
+- CapEx ties to DA schedule
+
+**Section 4: Retained Earnings**
+- RE roll-forward check: Prior RE + NI + SBC - Dividends = Ending RE
+- Show component breakdown for debugging
+
+**Section 5: Working Capital**
+- AR, Inventory, AP tie to BS
+- DSO, DIO, DPO reasonability checks (flag if outside normal ranges)
+
+**Section 6: Debt Schedule**
+- Total Debt ties to BS (Current + LT Debt)
+- Interest calculation ties to IS
+
+**Section 6b: Equity Financing**
+- Equity issuance proceeds tie to BS Common Stock/APIC increase
+- Cash increase from equity = Equity account increase (must balance)
+- Equity Raise Tie-Out: ΔCommon Stock/APIC (BS) = Equity Issuance (CFF) (must = 0)
+- Year 0 Equity Tie-Out: Equity Raised (Year 0) = Beginning Equity Capital (Year 1)
+
+**Section 6c: NOL Schedule**
+- Beginning NOL (Year 1 / Formation) = 0 (new business starts with zero NOL)
+- NOL increases only when EBT < 0 (losses must be realized to generate NOL)
+- DTA ties to BS (NOL Schedule DTA = BS Deferred Tax Asset)
+- NOL utilization ≤ 80% of EBT (post-2017 federal limitation)
+- NOL balance is non-negative (cannot utilize more than available)
+- NOL generated only when EBT < 0
+- Tax expense = 0 when taxable income ≤ 0
+
+**Section 7: Scenario Hierarchy**
+- Absolute metrics: Upside > Base > Downside (NI, EBITDA, FCF)
+- Margins: Upside > Base > Downside (GM%, EBITDA%, NI%)
+- Credit metrics: Upside < Base < Downside for leverage (inverted)
+
+**Section 8: Formula Integrity**
+- COGS, S&M, G&A, R&D, SBC driven by % of Revenue (no hardcodes)
+- Consistent formulas across projection years
+- No #REF!, #DIV/0!, #VALUE! errors
+
+**Section 9: Credit Metric Thresholds**
+- Flag metrics as Green/Yellow/Red based on covenant thresholds
+- Summary of any red flags
+
+### Master Check Formula
+
+Aggregate all section statuses into a single master check:
+- If all sections pass → "✓ ALL CHECKS PASS"
+- If any section fails → "✗ ERRORS DETECTED - REVIEW BELOW"
+
+### Quick Debug Workflow
+
+When Master Status shows errors:
+1. Scroll to find red-highlighted sections
+2. Identify which check category has failures
+3. Navigate to source tab to investigate
+4. Fix the underlying issue
+5. Return to Checks tab to verify resolution
+
+
+## Data sources — MCP first, web fallback
+
+Many passages below say "use the S&P Kensho MCP / Daloopa MCP / FactSet MCP". Those are commercial financial-data MCPs from the original Cowork plugin context. In Hermes:
+
+- **If you have any structured financial-data MCP configured** (Hermes supports MCP — see `native-mcp` skill), prefer it for point-in-time comps, precedent transactions, and filings.
+- **Otherwise**, fall back to:
+  - `web_search` / `web_extract` against SEC EDGAR (`https://www.sec.gov/cgi-bin/browse-edgar`) for US filings
+  - Company IR pages for press releases, earnings decks
+  - `browser_navigate` for interactive data portals
+  - User-provided data (explicitly ask when the context doesn't have it)
+- **Never fabricate**. If a multiple, precedent, or filing number can't be sourced, flag the cell as `[UNSOURCED]` and surface it to the user.
+
+## Attribution
+
+This skill is adapted from Anthropic's Claude for Financial Services plugin suite (Apache-2.0). The Office-JS / Cowork live-Excel paths have been removed; this version targets headless openpyxl via the `excel-author` skill's conventions. Original: https://github.com/anthropics/financial-services
diff --git a/optional-skills/finance/3-statement-model/references/formatting.md b/optional-skills/finance/3-statement-model/references/formatting.md
new file mode 100644
index 0000000000..1fbe938c16
--- /dev/null
+++ b/optional-skills/finance/3-statement-model/references/formatting.md
@@ -0,0 +1,118 @@
+# Formatting Standards Reference
+
+| Element | Format |
+|---------|--------|
+| Hard-coded inputs | Blue font |
+| Formulas | Black font |
+| Links to other sheets | Green font |
+| Check cells | Red if error, green if balanced |
+| Negative values | Parentheses, not minus signs |
+| Currency | No decimals for large figures, 2 decimals for per-share |
+| Percentages | 1 decimal place |
+| Headers | Bold, bottom border |
+| Units row | Include units row below headers ($ millions, %, etc.) |
+
+## Visual Separation Guidelines
+
+- Thin vertical border between historical and projected columns
+- Thick bottom border after section totals (e.g., Total Assets)
+- Single bottom border for subtotals
+- Double bottom border for grand totals
+
+## Total and Subtotal Row Formatting
+
+All total and subtotal rows must use **bold font formatting** for their numerical values to clearly distinguish aggregated figures from individual line items.
+
+### Income Statement (P&L) Tab
+| Row | Formatting |
+|-----|------------|
+| Gross Revenue | Bold |
+| Total Cost of Revenue | Bold |
+| Gross Profit | Bold |
+| Total SG&A | Bold |
+| EBITDA | Bold |
+| EBIT | Bold |
+| EBT | Bold |
+| Net Profit After Tax | Bold |
+
+### Balance Sheet Tab
+| Row | Formatting |
+|-----|------------|
+| Total Current Assets | Bold |
+| Total Non-Current Assets | Bold |
+| Total Other Assets | Bold |
+| Total Assets | Bold |
+| Total Current Liabilities | Bold |
+| Total Non-Current Liabilities | Bold |
+| Total Equity | Bold |
+| Total Liabilities and Equity | Bold |
+
+### Cash Flow Statement Tab
+| Row | Formatting |
+|-----|------------|
+| Cash Generated from Operations Before Working Capital Changes | Bold |
+| Total Working Capital Changes | Bold |
+| Net Cash Generated from Operations | Bold |
+| Net Cash Flow from Investing Activities | Bold |
+| Net Cash Flow from Financing Activities | Bold |
+| Closing Cash Balance | Bold |
+
+**Note:** This list is non-exhaustive. Apply bold formatting to any row that represents a total, subtotal, or summary calculation across the model.
+
+## Balance Sheet Check Row Formatting
+
+The Balance Sheet check row (below Total Liabilities and Equity) uses conditional number formatting that displays non-zero values in red. When the balance sheet balances correctly (check = 0), the values display in black or standard formatting.
+
+| Check Value | Font Color |
+|-------------|------------|
+| = 0 (balanced) | Black (standard) |
+| ≠ 0 (error) | Red |
+
+**Implementation:** Apply custom number format `[Red][<>0]0.00;[Red][<>0](0.00);0.00` or use Excel conditional formatting with the rule "Cell Value ≠ 0" → Red font.
+
+## Margin Row Formatting
+
+| Element | Format |
+|---------|--------|
+| Margin % rows | Indent, italics, 1 decimal place |
+| Positive trend | No special formatting (or subtle green) |
+| Negative trend | Flag for review (subtle yellow) |
+| Below peer average | Consider highlighting for discussion |
+
+## Credit Metric Formatting
+
+| Element | Format |
+|---------|--------|
+| Leverage multiples | 1 decimal with "x" suffix (e.g., 2.5x) |
+| Percentages | 1 decimal with "%" suffix |
+| Net Debt negative | Parentheses, indicates net cash position |
+| Section header | Bold, "CREDIT METRICS" |
+| Separator line | Thin border above credit metrics section |
+
+## Credit Metric Threshold Colors
+
+| Metric | Green | Yellow | Red |
+|--------|-------|--------|-----|
+| Total Debt / EBITDA | < 2.5x | 2.5x-4.0x | > 4.0x |
+| Net Debt / EBITDA | < 2.0x | 2.0x-3.5x | > 3.5x |
+| Interest Coverage | > 4.0x | 2.5x-4.0x | < 2.5x |
+| Debt / Total Cap | < 40% | 40%-60% | > 60% |
+| Current Ratio | > 1.5x | 1.0x-1.5x | < 1.0x |
+| Quick Ratio | > 1.0x | 0.75x-1.0x | < 0.75x |
+
+## Conditional Formatting for Checks Tab
+
+- Cell contains pass indicator → Green fill
+- Cell contains fail indicator → Red fill
+- Cell contains warning → Yellow fill
+- Difference cells = 0 → Light green fill
+- Difference cells ≠ 0 → Light red fill
+
+## Margin Reasonability Flags
+
+- Gross Margin < 0% → ERROR: Review COGS
+- Gross Margin > 80% → WARNING: Verify revenue/COGS
+- EBITDA Margin < 0% → FLAG: Operating losses
+- EBITDA Margin > 50% → WARNING: Unusually high
+- Net Margin < 0% → FLAG: Net losses (may be acceptable in growth phase)
+- Net Margin > Gross Margin → ERROR: Formula issue
diff --git a/optional-skills/finance/3-statement-model/references/formulas.md b/optional-skills/finance/3-statement-model/references/formulas.md
new file mode 100644
index 0000000000..db2645727e
--- /dev/null
+++ b/optional-skills/finance/3-statement-model/references/formulas.md
@@ -0,0 +1,292 @@
+# Formula Reference
+
+**IMPORTANT:** Use the formulas outlined in this reference document unless otherwise specified by the user.
+
+---
+
+## Core Linkages
+
+```
+Balance Sheet:        Assets = Liabilities + Equity
+Net Income:           IS Net Income → CF Operations (starting point)
+Cash Flow:            ΔCash = CFO + CFI + CFF
+Cash Tie-Out:         Ending Cash (CF) = Cash (BS Asset)
+Cash Monthly/Annual:  Closing Cash (Monthly) = Closing Cash (Annual)
+Retained Earnings:    Prior RE + Net Income - Dividends = Ending RE
+Equity Raise:         ΔCommon Stock/APIC (BS) = Equity Issuance (CFF)
+Year 0 Equity:        Equity Raised (Year 0) = Beginning Equity (Year 1)
+```
+
+## Gross Profit Calculation
+
+**IMPORTANT:** Gross Profit must be calculated from Net Revenue, not Gross Revenue.
+
+```
+Net Revenue - Cost of Revenue = Gross Profit
+```
+
+| Term | Definition |
+|------|------------|
+| Gross Revenue | Total revenue before any deductions |
+| Net Revenue | Gross Revenue - Returns - Allowances - Discounts |
+| Cost of Revenue | Direct costs attributable to production of goods/services sold |
+| Gross Profit | Net Revenue - Cost of Revenue |
+
+**Note:** Always use Net Revenue (also called "Net Sales" or simply "Revenue" on most financial statements) as the starting point for profitability calculations. Gross Revenue overstates the true top-line performance.
+
+## Margin Formulas
+
+```
+Gross Margin %      = Gross Profit / Net Revenue
+EBITDA              = EBIT + D&A  (or = Gross Profit - OpEx)
+EBITDA Margin %     = EBITDA / Net Revenue
+EBIT Margin %       = EBIT / Net Revenue
+Net Income Margin % = Net Income / Net Revenue
+```
+
+## Credit Metric Formulas
+
+```
+Total Debt            = Current Portion of Debt + Long-Term Debt
+Net Debt              = Total Debt - Cash
+Total Debt / EBITDA   = Total Debt / EBITDA (from IS)
+Net Debt / EBITDA     = Net Debt / EBITDA (from IS)
+Interest Coverage     = EBITDA / Interest Expense (from IS)
+Net Int Exp % Debt    = Net Interest Expense / Long-Term Debt
+Debt / Total Cap      = Total Debt / (Total Debt + Total Equity)
+Debt / Equity         = Total Debt / Total Equity
+Current Ratio         = Total Current Assets / Total Current Liabilities
+Quick Ratio           = (Total Current Assets - Inventory) / Total Current Liabilities
+```
+
+## Forecast Formulas (% of Net Revenue Method)
+
+```
+Cost of Revenue (Forecast) = Net Revenue × Cost of Revenue % Assumption
+S&M (Forecast)             = Net Revenue × S&M % Assumption
+G&A (Forecast)             = Net Revenue × G&A % Assumption
+R&D (Forecast)             = Net Revenue × R&D % Assumption
+SBC (Forecast)             = Net Revenue × SBC % Assumption
+```
+
+## Working Capital Formulas
+
+```
+Accounts Receivable
+  Prior AR
+  + Revenue (from IS)
+  - Cash Collections (plug)
+  = Ending AR
+  DSO = (AR / Revenue) × 365
+
+Inventory
+  Prior Inventory
+  + Purchases (plug)
+  - COGS (from IS)
+  = Ending Inventory
+  DIO = (Inventory / COGS) × 365
+
+Accounts Payable
+  Prior AP
+  + Purchases (from Inventory calc)
+  - Cash Payments (plug)
+  = Ending AP
+  DPO = (AP / COGS) × 365
+
+Net Working Capital = AR + Inventory - AP
+ΔWC = Current NWC - Prior NWC
+```
+
+## D&A Schedule Formulas
+
+```
+Beginning PP&E (Gross)
++ CapEx
+= Ending PP&E (Gross)
+
+Beginning Accumulated Depreciation
++ Depreciation Expense
+= Ending Accumulated Depreciation
+
+PP&E (Net) = Gross PP&E - Accumulated Depreciation
+```
+
+## Debt Schedule Formulas
+
+```
+Beginning Debt Balance
++ New Borrowings
+- Repayments
+= Ending Debt Balance
+
+Interest Expense = Avg Debt Balance × Interest Rate
+  (Use beginning balance to avoid circularity, or iterate if circular refs enabled)
+```
+
+## Retained Earnings Formula
+
+```
+Beginning Retained Earnings
++ Net Income (from IS)
++ Stock-Based Compensation (SBC) (from IS)
+- Dividends
+= Ending Retained Earnings
+```
+
+## NOL (Net Operating Loss) Schedule Formulas
+
+```
+NOL CARRYFORWARD SCHEDULE
+
+Beginning NOL Balance (Year 1 / Formation = 0)
++ NOL Generated (if EBT < 0, then ABS(EBT), else 0)
+- NOL Utilized (limited by taxable income and utilization cap)
+= Ending NOL Balance
+
+STARTING BALANCE RULE
+
+For a new business or first modeled period:
+  Beginning NOL Balance = 0
+  NOL can only increase through realized losses (EBT < 0)
+  NOL cannot be created from thin air or assumed
+
+NOL UTILIZATION CALCULATION
+
+Pre-Tax Income (EBT)
+  If EBT > 0:
+    NOL Available = Beginning NOL Balance
+    Utilization Limit = EBT × 80%  (post-2017 federal limit)
+    NOL Utilized = MIN(NOL Available, Utilization Limit)
+    Taxable Income = EBT - NOL Utilized
+  If EBT ≤ 0:
+    NOL Utilized = 0
+    Taxable Income = 0
+    NOL Generated = ABS(EBT)
+
+TAX CALCULATION WITH NOL
+
+Taxes Payable = MAX(0, Taxable Income × Tax Rate)
+  (Taxes cannot be negative; losses create NOL asset instead)
+
+DEFERRED TAX ASSET (DTA) FOR NOL
+
+DTA - NOL Carryforward = Ending NOL Balance × Tax Rate
+ΔDTA = Current DTA - Prior DTA
+  (Increase in DTA = non-cash benefit on CF)
+  (Decrease in DTA = non-cash expense on CF)
+```
+
+## Balance Sheet Structure
+
+```
+ASSETS
+  Cash (from CF ending cash)
+  Accounts Receivable (from WC)
+  Inventory (from WC)
+  Total Current Assets
+  
+  PP&E, Net (from DA)
+  Deferred Tax Asset - NOL (from NOL schedule)
+  Total Non-Current Assets
+  Total Assets
+
+LIABILITIES
+  Accounts Payable (from WC)
+  Current Portion of Debt (from Debt)
+  Total Current Liabilities
+  
+  Long-Term Debt (from Debt)
+  Total Liabilities
+
+EQUITY
+  Common Stock
+  Retained Earnings (from RE schedule)
+  Total Equity
+
+CHECK: Assets - Liabilities - Equity = 0
+```
+
+## Cash Flow Statement Structure
+
+```
+CASH FROM OPERATIONS (CFO)
+  Net Income (LINK: IS)
+  + D&A (LINK: DA schedule)
+  + Stock-Based Compensation (SBC) (LINK: IS or Assumptions)
+  - ΔDTA (Deferred Tax Asset) (LINK: NOL schedule; increase in DTA = use of cash)
+  - ΔAR (LINK: WC)
+  - ΔInventory (LINK: WC)
+  + ΔAP (LINK: WC)
+  = CFO
+
+CASH FROM INVESTING (CFI)
+  - CapEx (LINK: DA schedule)
+  = CFI
+
+CASH FROM FINANCING (CFF)
+  + Debt Issuance (LINK: Debt)
+  - Debt Repayment (LINK: Debt)
+  + Equity Issuance (LINK: BS Common Stock/APIC)
+  - Dividends (LINK: RE schedule)
+  = CFF
+
+Net Change in Cash = CFO + CFI + CFF
+Beginning Cash
++ Net Change in Cash
+= Ending Cash (LINK TO: BS Cash)
+```
+
+## Income Statement Structure
+
+```
+Net Revenue
+  Growth %
+(-) Cost of Revenue
+  % of Net Revenue
+────────────────
+Gross Profit (= Net Revenue - Cost of Revenue)
+  Gross Margin %
+
+(-) S&M
+  % of Net Revenue
+(-) G&A
+  % of Net Revenue
+(-) R&D
+  % of Net Revenue
+(-) D&A
+(-) SBC
+  % of Net Revenue
+────────────────
+EBIT
+  EBIT Margin %
+
+EBITDA
+  EBITDA Margin %
+
+(-) Interest Expense
+────────────────
+EBT (Pre-Tax Income)
+(-) NOL Utilization (from NOL schedule, reduces taxable income)
+────────────────
+Taxable Income
+(-) Taxes (Taxable Income × Tax Rate)
+────────────────
+Net Income
+  Net Income Margin %
+```
+
+## Check Formulas
+
+```
+BS Balance Check:       = Assets - Liabilities - Equity  (must = 0)
+Cash Tie-Out:           = BS Cash - CF Ending Cash       (must = 0)
+RE Roll-Forward:        = Prior RE + NI + SBC - Div - BS RE  (must = 0)
+DTA Tie-Out:            = NOL Schedule DTA - BS DTA      (must = 0)
+Equity Raise Tie-Out:   = ΔCommon Stock/APIC (BS) - Equity Issuance (CFF)  (must = 0)
+Year 0 Equity Tie-Out:  = Equity Raised (Year 0) - Beginning Equity (Year 1)  (must = 0)
+Cash Monthly vs Annual: = Closing Cash (Monthly) - Closing Cash (Annual)  (must = 0)
+NOL Utilization Cap:    = NOL Utilized ≤ EBT × 80%       (must be TRUE for post-2017)
+NOL Non-Negative:       = Ending NOL Balance ≥ 0         (must be TRUE)
+NOL Starting Balance:   = Beginning NOL (Year 1) = 0     (must be TRUE for new business)
+NOL Accumulation:       = NOL increases only when EBT < 0 (losses generate NOL)
+```
diff --git a/optional-skills/finance/3-statement-model/references/sec-filings.md b/optional-skills/finance/3-statement-model/references/sec-filings.md
new file mode 100644
index 0000000000..e0fa48453a
--- /dev/null
+++ b/optional-skills/finance/3-statement-model/references/sec-filings.md
@@ -0,0 +1,125 @@
+# SEC Filings Data Extraction Reference
+
+**When to Use:** Only reference this file when a model template specifically requires pulling data from SEC filings (10-K, 10-Q). For templates that provide data directly or use other data sources, this reference is not needed.
+
+---
+
+## Extracting Data from SEC Filings (10-K / 10-Q)
+
+When populating a model template with public company data, extract financials directly from SEC filings.
+
+### Step 1: Locate the Filing
+
+1. Use SEC EDGAR: `https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=[TICKER]&type=10-K`
+2. For quarterly data, use `type=10-Q`
+
+### Step 2: Identify Filing Currency
+
+Before extracting data, identify the reporting currency:
+- Check the cover page or header for reporting currency
+- Look at statement headers (e.g., "in thousands of U.S. dollars")
+- Review Note 1 (Summary of Significant Accounting Policies)
+
+**Common Currency Indicators**
+
+| Indicator | Currency |
+|-----------|----------|
+| $, USD | US Dollar |
+| €, EUR | Euro |
+| £, GBP | British Pound |
+| ¥, JPY | Japanese Yen |
+| ¥, CNY, RMB | Chinese Yuan |
+| CHF | Swiss Franc |
+| CAD, C$ | Canadian Dollar |
+
+Set model currency to match filing; document in Assumptions tab.
+
+### Step 3: Navigate to Financial Statements
+
+Within the 10-K or 10-Q, locate:
+- **Item 8** (10-K) or **Item 1** (10-Q): Financial Statements
+- Key sections to extract:
+  - Consolidated Statements of Operations (Income Statement)
+  - Consolidated Balance Sheets
+  - Consolidated Statements of Cash Flows
+  - Notes to Financial Statements (for schedule details)
+
+### Step 4: Data Extraction Mapping
+
+**Income Statement (from Consolidated Statements of Operations)**
+
+| Filing Line Item | Model Line Item |
+|------------------|-----------------|
+| Net revenues / Net sales | Revenue |
+| Cost of goods sold | COGS |
+| Selling, general and administrative | SG&A |
+| Depreciation and amortization | D&A |
+| Interest expense, net | Interest Expense |
+| Income tax expense | Taxes |
+| Net income | Net Income |
+
+**Balance Sheet (from Consolidated Balance Sheets)**
+
+| Filing Line Item | Model Line Item |
+|------------------|-----------------|
+| Cash and cash equivalents | Cash |
+| Accounts receivable, net | AR |
+| Inventories | Inventory |
+| Property, plant and equipment, net | PP&E (Net) |
+| Total assets | Total Assets |
+| Accounts payable | AP |
+| Short-term debt / Current portion of LT debt | Current Debt |
+| Long-term debt | LT Debt |
+| Retained earnings | Retained Earnings |
+| Total stockholders' equity | Total Equity |
+
+**Cash Flow Statement (from Consolidated Statements of Cash Flows)**
+
+| Filing Line Item | Model Line Item |
+|------------------|-----------------|
+| Net income | Net Income |
+| Depreciation and amortization | D&A |
+| Changes in accounts receivable | ΔAR |
+| Changes in inventories | ΔInventory |
+| Changes in accounts payable | ΔAP |
+| Capital expenditures | CapEx |
+| Proceeds from issuance of common stock | Equity Issuance |
+| Proceeds from / Repayments of debt | Debt activity |
+| Dividends paid | Dividends |
+
+### Step 5: Extract Supporting Detail from Notes
+
+For schedules, pull from Notes to Financial Statements:
+- **Note: Debt** → Maturity schedule, interest rates, covenants
+- **Note: Property, Plant & Equipment** → Gross PP&E, accumulated depreciation, useful lives
+- **Note: Revenue** → Segment breakdowns, geographic splits
+- **Note: Leases** → Operating vs. finance lease obligations
+
+### Step 6: Historical Data Requirements
+
+Extract 3 years of historical data minimum:
+- 10-K provides 3 years of IS/CF, 2 years of BS
+- For 3rd year BS, pull from prior year's 10-K
+- Use 10-Qs to fill in quarterly granularity if needed
+
+### Data Extraction Checklist
+
+- Identify reporting currency and scale (thousands, millions)
+- 3 years historical Income Statement
+- 3 years historical Cash Flow Statement
+- 3 years historical Balance Sheet
+- Verify IS Net Income = CF starting Net Income (each year)
+- Verify BS Cash = CF Ending Cash (each year)
+- Extract debt maturity schedule from notes
+- Extract D&A detail or useful life assumptions
+- Note any non-recurring / one-time items to normalize
+
+### Handling Common Filing Variations
+
+| Variation | How to Handle |
+|-----------|---------------|
+| D&A embedded in COGS/SG&A | Pull D&A from Cash Flow Statement |
+| "Other" line items are material | Check notes for breakdown |
+| Restatements | Use restated figures, note in assumptions |
+| Fiscal year ≠ calendar year | Label with fiscal year end (e.g., FYE Jan 2025) |
+| Non-USD reporting currency | Adapt model currency to match filing |
diff --git a/optional-skills/finance/comps-analysis/SKILL.md b/optional-skills/finance/comps-analysis/SKILL.md
new file mode 100644
index 0000000000..39c968d9af
--- /dev/null
+++ b/optional-skills/finance/comps-analysis/SKILL.md
@@ -0,0 +1,661 @@
+---
+name: comps-analysis
+description: Build comparable company analysis in Excel — operating metrics, valuation multiples, statistical benchmarking vs peer sets. Pairs with excel-author. Use for public-company valuation, IPO pricing, sector benchmarking, or outlier detection.
+version: 1.0.0
+author: Anthropic (adapted by Nous Research)
+license: Apache-2.0
+metadata:
+  hermes:
+    tags: [finance, valuation, comps, excel, openpyxl, modeling, investment-banking]
+    related_skills: [excel-author, pptx-author, dcf-model, lbo-model]
+---
+
+## Environment
+
+This skill assumes **headless openpyxl** — you are producing an .xlsx file on disk.
+Follow the `excel-author` skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables.
+Recalculate before delivery: `python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx`.
+
+# Comparable Company Analysis
+
+## ⚠️ CRITICAL: Data Source Priority (READ FIRST)
+
+**ALWAYS follow this data source hierarchy:**
+
+1. **FIRST: Check for MCP data sources** - If S&P Kensho MCP, FactSet MCP, or Daloopa MCP are available, use them exclusively for financial and trading information
+2. **DO NOT use web search** if the above MCP data sources are available
+3. **ONLY if MCPs are unavailable:** Then use Bloomberg Terminal, SEC EDGAR filings, or other institutional sources
+4. **NEVER use web search as a primary data source** - it lacks the accuracy, audit trails, and reliability required for institutional-grade analysis
+
+**Why this matters:** MCP sources provide verified, institutional-grade data with proper citations. Web search results can be outdated, inaccurate, or unreliable for financial analysis.
+
+---
+
+## Overview
+This skill teaches the agent to build institutional-grade comparable company analyses that combine operating metrics, valuation multiples, and statistical benchmarking. The output is a structured Excel/spreadsheet that enables informed investment decisions through peer comparison.
+
+**Reference Material & Contextualization:**
+
+An example comparable company analysis is provided in `examples/comps_example.xlsx`. When using this or other example files in this skill directory, use them intelligently:
+
+**DO use examples for:**
+- Understanding structural hierarchy (how sections flow)
+- Grasping the level of rigor expected (statistical depth, documentation standards)
+- Learning principles (clear headers, transparent formulas, audit trails)
+
+**DO NOT use examples for:**
+- Exact reproduction of format or metrics
+- Copying layout without considering context
+- Applying the same visual style regardless of audience
+
+**ALWAYS ask yourself first:**
+1. **"Do you have a preferred format or should I adapt the template style?"**
+2. **"Who is the audience?"** (Investment committee, board presentation, quick reference, detailed memo)
+3. **"What's the key question?"** (Valuation, growth analysis, competitive positioning, efficiency)
+4. **"What's the context?"** (M&A evaluation, investment decision, sector benchmarking, performance review)
+
+**Adapt based on specifics:**
+- **Industry context**: Big tech mega-caps need different metrics than emerging SaaS startups
+- **Sector-specific needs**: Add relevant metrics early (e.g., cloud ARR, enterprise customers, developer ecosystem for tech)
+- **Company familiarity**: Well-known companies may need less background, more focus on delta analysis
+- **Decision type**: M&A requires different emphasis than ongoing portfolio monitoring
+
+**Core principle:** Use template principles (clear structure, statistical rigor, transparent formulas) but vary execution based on context. The goal is institutional-quality analysis, not institutional-looking templates.
+
+User-provided examples and explicit preferences always take precedence over defaults.
+
+## Core Philosophy
+**"Build the right structure first, then let the data tell the story."**
+
+Start with headers that force strategic thinking about what matters, input clean data, build transparent formulas, and let statistics emerge automatically. A good comp should be immediately readable by someone who didn't build it.
+
+---
+
+## ⚠️ CRITICAL: Formulas Over Hardcodes + Step-by-Step Verification
+
+**Formulas, not hardcodes:**
+- Every derived value (margin, multiple, statistic) MUST be an Excel formula referencing input cells — never a pre-computed number pasted in
+- When using Python/openpyxl to build the sheet: write `cell.value = "=E7/C7"` (formula string), NOT `cell.value = 0.687` (computed result)
+- The only hardcoded values should be raw input data (revenue, EBITDA, share price, etc.) — and every one of those gets a cell comment with its source
+- Why: the model must update automatically when an input changes. A hardcoded margin is a silent bug waiting to happen.
+
+**Verify step-by-step with the user:**
+- After setting up the structure → show the user the header layout before filling data
+- After entering raw inputs → show the user the input block and confirm sources/periods before building formulas
+- After building operating metrics formulas → show the calculated margins and sanity-check with the user before moving to valuation
+- After building valuation multiples → show the multiples and confirm they look reasonable before adding statistics
+- Do NOT build the entire sheet end-to-end and then present it — catch errors early by confirming each section
+
+---
+
+## Section 1: Document Structure & Setup
+
+### Header Block (Rows 1-3)
+```
+Row 1: [ANALYSIS TITLE] - COMPARABLE COMPANY ANALYSIS
+Row 2: [List of Companies with Tickers] • [Company 1 (TICK1)] • [Company 2 (TICK2)] • [Company 3 (TICK3)]
+Row 3: As of [Period] | All figures in [USD Millions/Billions] except per-share amounts and ratios
+```
+
+**Why this matters:** Establishes context immediately. Anyone opening this file knows what they're looking at, when it was created, and how to interpret the numbers.
+
+### Visual Convention Standards (OPTIONAL - User preferences and uploaded templates always override)
+
+**IMPORTANT: These are suggested defaults only. Always prioritize:**
+1. User's explicit formatting preferences
+2. Formatting from any uploaded template files
+3. Company/team style guides
+4. These defaults (only if no other guidance provided)
+
+**Suggested Font & Typography:**
+- **Font family**: Times New Roman (professional, readable, industry standard)
+- **Font size**: 11pt for data cells, 12pt for headers
+- **Bold text**: Section headers, company names, statistic labels
+
+**Default Color & Shading — Professional Blue/Grey Palette (minimal is better):**
+- **Keep it restrained** — only blues and greys. Do NOT introduce greens, oranges, reds, or multiple accent colors. A clean comps sheet uses 3-4 colors total.
+- **Section headers** (e.g., "OPERATING STATISTICS & FINANCIAL METRICS"):
+  - Dark blue background (`#1F4E79` or `#17365D` navy)
+  - White bold text
+  - Full row shading across all columns
+- **Column headers** (e.g., "Company", "Revenue", "Margin"):
+  - Light blue background (`#D9E1F2` or similar pale blue)
+  - Black bold text
+  - Centered alignment
+- **Data rows**:
+  - White background for company data
+  - Black text for formulas; blue text for hardcoded inputs
+- **Statistics rows** (Maximum, 75th Percentile, etc.):
+  - Light grey background (`#F2F2F2`)
+  - Black text, left-aligned labels
+- **That's the whole palette**: dark blue + light blue + light grey + white. Nothing else unless the user's template says otherwise.
+
+**Suggested Formatting Conventions:**
+- **Decimal precision**:
+  - Percentages: 1 decimal (12.3%)
+  - Multiples: 1 decimal (13.5x)
+  - Dollar amounts: No decimals, thousands separator (69,632)
+  - Margins shown as percentages: 1 decimal (68.7%)
+- **Borders**: No borders (clean, minimal appearance)
+- **Alignment**: All metrics center-aligned for clean, uniform appearance
+- **Cell dimensions**: All column widths should be uniform/even, all row heights should be consistent (creates clean, professional grid)
+
+**Note:** If the user provides a template file or specifies different formatting, use that instead.
+
+---
+
+## Section 2: Operating Statistics & Financial Metrics
+
+### Core Columns (Start with these)
+1. **Company** - Names with consistent formatting
+2. **Revenue** - Size metric (can be LTM, quarterly, or annual depending on context)
+3. **Revenue Growth** - Year-over-year percentage change
+4. **Gross Profit** - Revenue minus cost of goods sold
+5. **Gross Margin** - GP/Revenue (fundamental profitability)
+6. **EBITDA** - Earnings before interest, tax, depreciation, amortization
+7. **EBITDA Margin** - EBITDA/Revenue (operating efficiency)
+
+### Optional Additions (Choose based on industry/purpose)
+- **Quarterly vs LTM** - Include both if seasonality matters
+- **Free Cash Flow** - For capital-intensive or SaaS businesses
+- **FCF Margin** - FCF/Revenue (cash generation efficiency)
+- **Net Income** - For mature, profitable companies
+- **Operating Income** - For businesses with varying D&A
+- **CapEx metrics** - For asset-heavy industries
+- **Rule of 40** - Specifically for SaaS (Growth % + Margin %)
+- **FCF Conversion** - For quality of earnings analysis (advanced)
+
+### Formula Examples (Using Row 7 as example)
+```excel
+// Core ratios - these are always calculated
+Gross Margin (F7): =E7/C7
+EBITDA Margin (H7): =G7/C7
+
+// Optional ratios - include if relevant
+FCF Margin: =[FCF]/[Revenue]
+Net Margin: =[Net Income]/[Revenue]
+Rule of 40: =[Growth %]+[FCF Margin %]
+```
+
+**Golden Rule:** Every ratio should be [Something] / [Revenue] or [Something] / [Something from this sheet]. Keep it simple.
+
+### Statistics Block (After company data)
+
+**CRITICAL: Add statistics formulas for all comparable metrics (ratios, margins, growth rates, multiples).**
+
+```
+[Leave one blank row for visual separation]
+- Maximum: =MAX(B7:B9)
+- 75th Percentile: =QUARTILE(B7:B9,3)
+- Median: =MEDIAN(B7:B9)
+- 25th Percentile: =QUARTILE(B7:B9,1)
+- Minimum: =MIN(B7:B9)
+```
+
+**Columns that NEED statistics (comparable metrics):**
+- Revenue Growth %, Gross Margin %, EBITDA Margin %, EPS
+- EV/Revenue, EV/EBITDA, P/E, Dividend Yield %, Beta
+
+**Columns that DON'T need statistics (size metrics):**
+- Revenue, EBITDA, Net Income (absolute size varies by company scale)
+- Market Cap, Enterprise Value (not comparable across different-sized companies)
+
+**Note:** Add one blank row between company data and statistics rows for visual separation. Do NOT add a "SECTOR STATISTICS" or "VALUATION STATISTICS" header row.
+
+**Why quartiles matter:** They show distribution, not just average. A 75th percentile multiple tells you what "premium" companies trade at.
+
+---
+
+## Section 3: Valuation Multiples & Investment Metrics
+
+### Core Valuation Columns (Start with these)
+1. **Company** - Same order as operating section
+2. **Market Cap** - Current market valuation
+3. **Enterprise Value** - Market Cap ± Net Debt/Cash
+4. **EV/Revenue** - How much market pays per dollar of sales
+5. **EV/EBITDA** - How much market pays per dollar of earnings
+6. **P/E Ratio** - Price relative to net earnings
+
+### Optional Valuation Metrics (Choose based on context)
+- **FCF Yield** - FCF/Market Cap (for cash-focused analysis)
+- **PEG Ratio** - P/E/Growth Rate (for growth companies)
+- **Price/Book** - Market value vs. book value (for asset-heavy businesses)
+- **ROE/ROA** - Return metrics (for profitability comparison)
+- **Revenue/EBITDA CAGR** - Historical growth rates (for trend analysis)
+- **Asset Turnover** - Revenue/Assets (for operational efficiency)
+- **Debt/Equity** - Leverage (for capital structure analysis)
+
+**Key Principle:** Include 3-5 core multiples that matter for your industry. Don't include every possible metric just because you can.
+
+### Formula Examples
+```excel
+// Core multiples - always include these
+EV/Revenue: =[Enterprise Value]/[LTM Revenue]
+EV/EBITDA: =[Enterprise Value]/[LTM EBITDA]
+P/E Ratio: =[Market Cap]/[Net Income]
+
+// Optional multiples - include if data available
+FCF Yield: =[LTM FCF]/[Market Cap]
+PEG Ratio: =[P/E]/[Growth Rate %]
+```
+
+### Cross-Reference Rule
+**CRITICAL:** Valuation multiples MUST reference the operating metrics section. Never input the same raw data twice. If revenue is in C7, then EV/Revenue formula should reference C7.
+
+### Statistics Block
+Same structure as operating section: Max, 75th, Median, 25th, Min for every metric. Add one blank row for visual separation between company data and statistics. Do NOT add a "VALUATION STATISTICS" header row.
+
+---
+
+## Section 4: Notes & Methodology Documentation
+
+### Required Components
+
+**Data Sources & Quality:**
+- Where did the data come from? (S&P Kensho MCP, FactSet MCP, Daloopa MCP, Bloomberg, SEC filings)
+- What period does it cover? (Q4 2024, audited figures)
+- How was it verified? (Cross-checked against 10-K/10-Q)
+- Note: Prioritize MCP data sources (S&P Kensho, FactSet, Daloopa) if available for better accuracy and traceability
+
+**Key Definitions:**
+- EBITDA calculation method (Gross Profit + D&A, or Operating Income + D&A)
+- Free Cash Flow formula (Operating CF - CapEx)
+- Special metrics explained (Rule of 40, FCF Conversion)
+- Time period definitions (LTM, CAGR calculation periods)
+
+**Valuation Methodology:**
+- How was Enterprise Value calculated? (Market Cap + Net Debt)
+- What growth rates were used? (Historical CAGR, forward estimates)
+- Any adjustments made? (One-time items excluded, normalized margins)
+
+**Analysis Framework:**
+- What's the investment thesis? (Cloud/SaaS efficiency)
+- What metrics matter most? (Cash generation, capital efficiency)
+- How should readers interpret the statistics? (Quartiles provide context)
+
+---
+
+## Section 5: Choosing the Right Metrics (Decision Framework)
+
+### Start with "What question am I answering?"
+
+**"Which company is undervalued?"**
+→ Focus on: EV/Revenue, EV/EBITDA, P/E, Market Cap
+→ Skip: Operational details, growth metrics
+
+**"Which company is most efficient?"**
+→ Focus on: Gross Margin, EBITDA Margin, FCF Margin, Asset Turnover
+→ Skip: Size metrics, absolute dollar amounts
+
+**"Which company is growing fastest?"**
+→ Focus on: Revenue Growth %, EBITDA CAGR, User/Customer Growth
+→ Skip: Margin metrics, leverage ratios
+
+**"Which is the best cash generator?"**
+→ Focus on: FCF, FCF Margin, FCF Conversion, CapEx intensity
+→ Skip: EBITDA, P/E ratios
+
+### Industry-Specific Metric Selection
+
+**Software/SaaS:**
+Must have: Revenue Growth, Gross Margin, Rule of 40
+Optional: ARR, Net Dollar Retention, CAC Payback
+Skip: Asset Turnover, Inventory metrics
+
+**Manufacturing/Industrials:**
+Must have: EBITDA Margin, Asset Turnover, CapEx/Revenue
+Optional: ROA, Inventory Turns, Backlog
+Skip: Rule of 40, SaaS metrics
+
+**Financial Services:**
+Must have: ROE, ROA, Efficiency Ratio, P/E
+Optional: Net Interest Margin, Loan Loss Reserves
+Skip: Gross Margin, EBITDA (not meaningful for banks)
+
+**Retail/E-commerce:**
+Must have: Revenue Growth, Gross Margin, Inventory Turnover
+Optional: Same-Store Sales, Customer Acquisition Cost
+Skip: Heavy R&D or CapEx metrics
+
+### The "5-10 Rule"
+
+**5 operating metrics** - Revenue, Growth, 2-3 margins/efficiency metrics
+**5 valuation metrics** - Market Cap, EV, 3 multiples
+**= 10 total columns** - Enough to tell the story, not so many you lose the thread
+
+If you have more than 15 metrics, you're probably including noise. Edit ruthlessly.
+
+---
+
+## Section 6: Best Practices & Quality Checks
+
+### Before You Start
+1. **Define the peer group** - Companies must be truly comparable (similar business model, scale, geography)
+2. **Choose the right period** - LTM smooths seasonality; quarterly shows trends
+3. **Standardize units upfront** - Millions vs. billions decision affects everything
+4. **Map data sources** - Know where each number comes from
+
+### As You Build
+1. **Input all raw data first** - Complete the blue text before writing formulas
+2. **Add cell comments to ALL hard-coded inputs** - Right-click cell → Insert Comment → Document source OR assumption
+
+   **For sourced data, cite exactly where it came from:**
+   - Example: "Bloomberg Terminal - MSFT Equity DES, accessed 2024-10-02"
+   - Example: "Q4 2024 10-K filing, page 42, line item 'Total Revenue'"
+   - Example: "FactSet consensus estimate as of 2024-10-02"
+   - **Include hyperlinks when possible**: Right-click cell → Link → paste URL to SEC filing, data source, or report
+
+   **For assumptions, explain the reasoning:**
+   - Example: "Assumed 15% EBITDA margin based on peer median, company does not disclose"
+   - Example: "Estimated Enterprise Value as Market Cap + $50M net debt (from Q3 balance sheet, Q4 not yet available)"
+   - Example: "Forward P/E based on street consensus EPS of $3.45 (average of 12 analyst estimates)"
+
+   **Why this matters**: Enables audit trails, data verification, assumption transparency, and future updates
+3. **Build formulas row by row** - Test each calculation before moving on
+4. **Use absolute references for headers** - $C$6 locks the header row
+5. **Format consistently** - Percentages as percentages, not decimals
+6. **Add conditional formatting** - Highlight outliers automatically
+
+### Sanity Checks
+- **Margin test**: Gross margin > EBITDA margin > Net margin (always true by definition)
+- **Multiple reasonableness**: 
+  - EV/Revenue: typically 0.5-20x (varies widely by industry)
+  - EV/EBITDA: typically 8-25x (fairly consistent across industries)
+  - P/E: typically 10-50x (depends on growth rate)
+- **Growth-multiple correlation**: Higher growth usually means higher multiples
+- **Size-efficiency trade-off**: Larger companies often have better margins (scale benefits)
+
+### Common Mistakes to Avoid
+❌ Mixing market cap and enterprise value in formulas
+❌ Using different time periods for numerator and denominator (LTM vs quarterly)
+❌ Hardcoding numbers into formulas instead of cell references
+❌ **Hard-coded inputs without cell comments citing the source OR explaining the assumption**
+❌ Missing hyperlinks to SEC filings or data sources when available
+❌ Including too many metrics without clear purpose
+❌ Including non-comparable companies (different business models)
+❌ Using outdated data without disclosure
+❌ Calculating averages of percentages incorrectly (should be median)
+
+---
+
+## Section 6: Advanced Features
+
+### Dynamic Headers
+For columns showing calculations, use clear unit labels:
+```
+Revenue Growth (YoY) % | EBITDA Margin | FCF Margin | Rule of 40
+```
+
+### Quartile Analysis Benefits
+Instead of just mean/median, quartiles show:
+- **75th percentile** = "Premium" companies trade here
+- **Median** = Typical market valuation
+- **25th percentile** = "Discount" territory
+
+This helps answer: "Is our target company trading rich or cheap vs. peers?"
+
+### Industry-Specific Modifications
+
+**Software/SaaS:**
+- Add: ARR, Net Dollar Retention, CAC Payback Period
+- Emphasize: Rule of 40, FCF margins, gross margins >70%
+
+**Healthcare:**
+- Add: R&D/Revenue, Pipeline value, Regulatory status
+- Emphasize: EBITDA margins, growth rates, reimbursement risk
+
+**Industrials:**
+- Add: Backlog, Order book trends, Geographic mix
+- Emphasize: ROIC, asset turnover, cyclical adjustments
+
+**Consumer:**
+- Add: Same-store sales, Customer acquisition cost, Brand value
+- Emphasize: Revenue growth, gross margins, inventory turns
+
+---
+
+## Section 7: Workflow & Practical Tips
+
+### Step-by-Step Process
+1. **Set up structure** (30 minutes)
+   - Create all headers
+   - Format cells (blue for inputs, black for formulas)
+   - Lock in units and date references
+
+2. **Gather data** (60-90 minutes)
+   - Pull from primary sources (S&P Kensho MCP, FactSet MCP, Daloopa MCP if available; otherwise Bloomberg, SEC)
+   - Input all raw numbers in blue
+   - Document sources in notes section
+
+3. **Build formulas** (30 minutes)
+   - Start with simple ratios (margins)
+   - Progress to multiples (EV/Revenue)
+   - Add cross-checks (do margins make sense?)
+
+4. **Add statistics** (15 minutes)
+   - Copy formula structure for all columns
+   - Verify ranges are correct (B7:B9, not B7:B10)
+   - Check quartile logic
+
+5. **Quality control** (30 minutes)
+   - Run sanity checks
+   - Verify formula references
+   - Check for #DIV/0! or #REF! errors
+   - Compare against known benchmarks
+
+6. **Documentation** (15 minutes)
+   - Complete notes section
+   - Add data sources
+   - Define methodologies
+   - Date-stamp the analysis
+
+### Pro Tips
+- **Save templates**: Build once, reuse forever
+- **Color-code outliers**: Conditional formatting for values >2 standard deviations
+- **Link to source files**: Hyperlink to Bloomberg screenshots or SEC filings
+- **Version control**: Save as "Comps_v1_2024-12-15" with clear dating
+- **Collaborative reviews**: Have someone else check your formulas
+
+### Excel Formatting Checklist (Optional - adapt to user preferences)
+- [ ] Font set to user's preferred style (default: Times New Roman, 11pt data, 12pt headers)
+- [ ] Section headers formatted per user's template (default: dark blue #17365D with white bold text)
+- [ ] Column headers formatted per user's template (default: light blue/gray #D9E2F3 with black bold text)
+- [ ] Statistics rows formatted per user's template (default: light gray #F2F2F2)
+- [ ] No borders applied (clean, minimal appearance)
+- [ ] **Column widths set to uniform/even width** (creates clean, professional appearance)
+- [ ] **Row heights set to consistent height** (typically 20-25pt for data rows)
+- [ ] Numbers formatted with proper decimal precision and thousands separators
+- [ ] **All metrics center-aligned** for clean, uniform appearance
+- [ ] **One blank row for separation between company data and statistics rows**
+- [ ] **No separate "SECTOR STATISTICS" or "VALUATION STATISTICS" header rows**
+- [ ] **Every hard-coded input cell has a comment with either: (1) exact data source, OR (2) assumption explanation**
+- [ ] **Hyperlinks added to cells where applicable** (SEC filings, data provider pages, reports)
+
+---
+
+## Section 8: Example Template Layout
+
+**Simple Version (Start here):**
+```
+┌─────────────────────────────────────────────────────────────┐
+│ TECHNOLOGY - COMPARABLE COMPANY ANALYSIS                    │
+│ Microsoft • Alphabet • Amazon                               │
+│ As of Q4 2024 | All figures in USD Millions                │
+├─────────────────────────────────────────────────────────────┤
+│ OPERATING METRICS                                           │
+├──────────┬─────────┬─────────┬──────────┬──────────────────┤
+│ Company  │ Revenue │ Growth  │ Gross    │ EBITDA  │ EBITDA │
+│          │ (LTM)   │ (YoY)   │ Margin   │ (LTM)   │ Margin │
+├──────────┼─────────┼─────────┼──────────┼─────────┼────────┤
+│ MSFT     │ 261,400 │ 12.3%   │ 68.7%    │ 205,100 │ 78.4%  │
+│ GOOGL    │ 349,800 │ 11.8%   │ 57.9%    │ 239,300 │ 68.4%  │
+│ AMZN     │ 638,100 │ 10.5%   │ 47.3%    │ 152,600 │ 23.9%  │
+│          │         │         │          │         │        │ [blank row]
+│ Median   │ =MEDIAN │ =MEDIAN │ =MEDIAN  │ =MEDIAN │=MEDIAN │
+│ 75th %   │ =QUART  │ =QUART  │ =QUART   │ =QUART  │=QUART  │
+│ 25th %   │ =QUART  │ =QUART  │ =QUART   │ =QUART  │=QUART  │
+├─────────────────────────────────────────────────────────────┤
+│ VALUATION MULTIPLES                                         │
+├──────────┬──────────┬──────────┬──────────┬────────────────┤
+│ Company  │ Mkt Cap  │ EV       │ EV/Rev   │ EV/EBITDA │ P/E│
+├──────────┼──────────┼──────────┼──────────┼───────────┼────┤
+│ MSFT     │3,550,000 │3,530,000 │ 13.5x    │ 17.2x     │36.0│
+│ GOOGL    │2,030,000 │1,960,000 │  5.6x    │  8.2x     │24.5│
+│ AMZN     │2,226,000 │2,320,000 │  3.6x    │ 15.2x     │58.3│
+│          │          │          │          │           │    │ [blank row]
+│ Median   │ =MEDIAN  │ =MEDIAN  │ =MEDIAN  │ =MEDIAN   │=MED│
+│ 75th %   │ =QUART   │ =QUART   │ =QUART   │ =QUART    │=QRT│
+│ 25th %   │ =QUART   │ =QUART   │ =QUART   │ =QUART    │=QRT│
+└──────────┴──────────┴──────────┴──────────┴───────────┴────┘
+```
+
+**Add complexity only when needed:**
+- Include quarterly AND LTM if seasonality matters
+- Add FCF metrics if cash generation is key story
+- Include industry-specific metrics (Rule of 40 for SaaS, etc.)
+- Add more statistics rows if you have >5 companies
+
+---
+
+## Section 9: Industry-Specific Additions (Optional)
+
+Only add these if they're critical to your analysis. Most comps work fine with just core metrics.
+
+**Software/SaaS:**
+Add if relevant: ARR, Net Dollar Retention, Rule of 40
+
+**Financial Services:**
+Add if relevant: ROE, Net Interest Margin, Efficiency Ratio
+
+**E-commerce:**
+Add if relevant: GMV, Take Rate, Active Buyers
+
+**Healthcare:**
+Add if relevant: R&D/Revenue, Pipeline Value, Patent Timeline
+
+**Manufacturing:**
+Add if relevant: Asset Turnover, Inventory Turns, Backlog
+
+---
+
+## Section 10: Red Flags & Warning Signs
+
+### Data Quality Issues
+🚩 Inconsistent time periods (mixing quarterly and annual)  
+🚩 Missing data without explanation  
+🚩 Significant differences between data sources (>10% variance)
+
+### Valuation Red Flags
+🚩 Negative EBITDA companies being valued on EBITDA multiples (use revenue multiples instead)  
+🚩 P/E ratios >100x without hypergrowth story  
+🚩 Margins that don't make sense for the industry
+
+### Comparability Issues
+🚩 Different fiscal year ends (causes timing problems)  
+🚩ixing pure-play and conglomerates  
+🚩 Materially different business models labeled as "comps"
+
+**When in doubt, exclude the company.** Better to have 3 perfect comps than 6 questionable ones.
+
+---
+
+## Section 11: Formulas Reference Guide
+
+### Essential Excel Formulas
+```excel
+// Statistical Functions
+=AVERAGE(range)          // Simple mean
+=MEDIAN(range)           // Middle value
+=QUARTILE(range, 1)      // 25th percentile
+=QUARTILE(range, 3)      // 75th percentile
+=MAX(range)              // Maximum value
+=MIN(range)              // Minimum value
+=STDEV.P(range)          // Standard deviation
+
+// Financial Calculations
+=B7/C7                   // Simple ratio (Margin)
+=SUM(B7:B9)/3            // Average of multiple companies
+=IF(B7>0, C7/B7, "N/A")  // Conditional calculation
+=IFERROR(C7/D7, 0)       // Handle divide by zero
+
+// Cross-Sheet References
+='Sheet1'!B7             // Reference another sheet
+=VLOOKUP(A7, Table1, 2)  // Lookup from data table
+=INDEX(MATCH())          // Advanced lookup
+
+// Formatting
+=TEXT(B7, "0.0%")        // Format as percentage
+=TEXT(C7, "#,##0")       // Thousands separator
+```
+
+### Common Ratio Formulas
+```excel
+Gross Margin = Gross Profit / Revenue
+EBITDA Margin = EBITDA / Revenue
+FCF Margin = Free Cash Flow / Revenue
+FCF Conversion = FCF / Operating Cash Flow
+ROE = Net Income / Shareholders' Equity
+ROA = Net Income / Total Assets
+Asset Turnover = Revenue / Total Assets
+Debt/Equity = Total Debt / Shareholders' Equity
+```
+
+---
+
+## Key Principles Summary
+
+1. **Structure drives insight** - Right headers force right thinking
+2. **Less is more** - 5-10 metrics that matter beat 20 that don't
+3. **Choose metrics for your question** - Valuation analysis ≠ efficiency analysis
+4. **Statistics show patterns** - Median/quartiles reveal more than average
+5. **Transparency beats complexity** - Simple formulas everyone understands
+6. **Comparability is king** - Better to exclude than force a bad comp
+7. **Document your choices** - Explain which metrics and why in notes section
+
+---
+
+## Output Checklist
+
+Before delivering a comp analysis, verify:
+- [ ] All companies are truly comparable
+- [ ] Data is from consistent time periods
+- [ ] Units are clearly labeled (millions/billions)
+- [ ] Formulas reference cells, not hardcoded values
+- [ ] **All hard-coded input cells have comments with either: (1) exact data source with citation, OR (2) clear assumption with explanation**
+- [ ] **Hyperlinks added where relevant** (SEC EDGAR filings, Bloomberg pages, research reports)
+- [ ] Statistics include at least 5 metrics (Max, 75th, Med, 25th, Min)
+- [ ] Notes section documents sources and methodology
+- [ ] Visual formatting follows conventions (blue = input, black = formula)
+- [ ] Sanity checks pass (margins logical, multiples reasonable)
+- [ ] Date stamp is current ("As of [Date]")
+- [ ] Formula auditing shows no errors (#DIV/0!, #REF!, #N/A)
+
+---
+
+## Continuous Improvement
+
+After completing a comp analysis, ask:
+1. Did the statistics reveal unexpected insights?
+2. Were there any data gaps that limited analysis?
+3. Did stakeholders ask for metrics you didn't include?
+4. How long did it take vs. how long should it take?
+5. What would make this more useful next time?
+
+The best comp analyses evolve with each iteration. Save templates, learn from feedback, and refine the structure based on what decision-makers actually use.
+
+
+## Data sources — MCP first, web fallback
+
+Many passages below say "use the S&P Kensho MCP / Daloopa MCP / FactSet MCP". Those are commercial financial-data MCPs from the original Cowork plugin context. In Hermes:
+
+- **If you have any structured financial-data MCP configured** (Hermes supports MCP — see `native-mcp` skill), prefer it for point-in-time comps, precedent transactions, and filings.
+- **Otherwise**, fall back to:
+  - `web_search` / `web_extract` against SEC EDGAR (`https://www.sec.gov/cgi-bin/browse-edgar`) for US filings
+  - Company IR pages for press releases, earnings decks
+  - `browser_navigate` for interactive data portals
+  - User-provided data (explicitly ask when the context doesn't have it)
+- **Never fabricate**. If a multiple, precedent, or filing number can't be sourced, flag the cell as `[UNSOURCED]` and surface it to the user.
+
+## Attribution
+
+This skill is adapted from Anthropic's Claude for Financial Services plugin suite (Apache-2.0). The Office-JS / Cowork live-Excel paths have been removed; this version targets headless openpyxl via the `excel-author` skill's conventions. Original: https://github.com/anthropics/financial-services
diff --git a/optional-skills/finance/dcf-model/SKILL.md b/optional-skills/finance/dcf-model/SKILL.md
new file mode 100644
index 0000000000..75a9d7de5f
--- /dev/null
+++ b/optional-skills/finance/dcf-model/SKILL.md
@@ -0,0 +1,1269 @@
+---
+name: dcf-model
+description: Build institutional-quality DCF valuation models in Excel — revenue projections, FCF build, WACC, terminal value, Bear/Base/Bull scenarios, 5x5 sensitivity tables. Pairs with excel-author. Use for intrinsic-value equity analysis.
+version: 1.0.0
+author: Anthropic (adapted by Nous Research)
+license: Apache-2.0
+metadata:
+  hermes:
+    tags: [finance, valuation, dcf, excel, openpyxl, modeling, investment-banking]
+    related_skills: [excel-author, pptx-author, comps-analysis, lbo-model, 3-statement-model]
+---
+
+## Environment
+
+This skill assumes **headless openpyxl** — you are producing an .xlsx file on disk.
+Follow the `excel-author` skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables.
+Recalculate before delivery: `python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx`.
+
+# DCF Model Builder
+
+## Overview
+
+This skill creates institutional-quality DCF models for equity valuation following investment banking standards. Each analysis produces a detailed Excel model (with sensitivity analysis included at the bottom of the DCF sheet).
+
+## Tools
+
+- Default to using all of the information provided by the user and MCP servers available for data sourcing.
+
+## Critical Constraints - Read These First
+
+These constraints apply throughout all DCF model building. Review before starting:
+
+**Formulas Over Hardcodes (NON-NEGOTIABLE):**
+- Every projection, margin, discount factor, PV, and sensitivity cell MUST be a live Excel formula — never a value computed in Python and written as a number
+- When using openpyxl: `ws["D20"] = "=D19*(1+$B$8)"` is correct; `ws["D20"] = calculated_revenue` is WRONG
+- The only hardcoded numbers permitted are: (1) raw historical inputs, (2) assumption drivers (growth rates, WACC inputs, terminal g), (3) current market data (share price, debt balance)
+- If you catch yourself computing something in Python and writing the result — STOP. The model must flex when the user changes an assumption.
+
+**Verify Step-by-Step With the User (DO NOT build end-to-end):**
+- After data retrieval → show the user the raw inputs block (revenue, margins, shares, net debt) and confirm before projecting
+- After revenue projections → show the projected top line and growth rates, confirm before building margin build
+- After FCF build → show the full FCF schedule, confirm logic before computing WACC
+- After WACC → show the calculation and inputs, confirm before discounting
+- After terminal value + PV → show the equity bridge (EV → equity value → per share), confirm before sensitivity tables
+- Catch errors at each stage — a wrong margin assumption discovered after sensitivity tables are built means rebuilding everything downstream
+
+**Sensitivity Tables:**
+- **Use an ODD number of rows and columns** (standard: 5×5, sometimes 7×7) — this guarantees a true center cell
+- **Center cell = base case.** Build the axis values so the middle row header and middle column header exactly equal the model's actual assumptions (e.g., if base WACC = 9.0%, the middle row is 9.0%; if terminal g = 3.0%, the middle column is 3.0%). The center cell's output must therefore equal the model's actual implied share price — this is the sanity check that the table is built correctly.
+- **Highlight the center cell** with the medium-blue fill (`#BDD7EE`) + bold font so it's immediately visible which cell is the base case.
+- Populate ALL cells (typically 3 tables × 25 cells = 75) with full DCF recalculation formulas
+- Use openpyxl loops to write formulas programmatically
+- NO placeholder text, NO linear approximations, NO manual steps required
+- Each cell must recalculate full DCF for that assumption combination
+
+**Cell Comments:**
+- Add cell comments AS each hardcoded value is created
+- Format: "Source: [System/Document], [Date], [Reference], [URL if applicable]"
+- Every blue input must have a comment before moving to next section
+- Do not defer to end or write "TODO: add source"
+
+**Model Layout Planning:**
+- Define ALL section row positions BEFORE writing any formulas
+- Write ALL headers and labels first
+- Write ALL section dividers and blank rows second
+- THEN write formulas using the locked row positions
+- Test formulas immediately after creation
+
+**Formula Recalculation:**
+- Run `python recalc.py model.xlsx 30` before delivery
+- Fix ALL errors until status is "success"
+- Zero formula errors required (#REF!, #DIV/0!, #VALUE!, etc.)
+
+**Scenario Blocks:**
+- Create separate blocks for Bear/Base/Bull cases
+- Show assumptions horizontally across projection years within each block
+- Use IF formulas: `=IF($B$6=1,[Bear cell],IF($B$6=2,[Base cell],[Bull cell]))`
+- Verify formulas reference correct scenario block cells
+
+## DCF Process Workflow
+
+### Step 1: Data Retrieval and Validation
+
+Fetch data from MCP servers, user provided data, and the web.
+
+**Data Sources Priority:**
+1. **MCP Servers** (if configured) - Structured financial data from providers like Daloopa
+2. **User-Provided Data** - Historical financials from their research
+3. **Web Search/Fetch** - Current prices, beta, debt and cash when needed
+
+**Validation Checklist:**
+- Verify net debt vs net cash (critical for valuation)
+- Confirm diluted shares outstanding (check for recent buybacks/issuances)
+- Validate historical margins are consistent with business model
+- Cross-check revenue growth rates with industry benchmarks
+- Verify tax rate is reasonable (typically 21-28%)
+
+### Step 2: Historical Analysis (3-5 years)
+
+Analyze and document:
+- **Revenue growth trends**: Calculate CAGR, identify drivers
+- **Margin progression**: Track gross margin, EBIT margin, FCF margin
+- **Capital intensity**: D&A and CapEx as % of revenue
+- **Working capital efficiency**: NWC changes as % of revenue growth
+- **Return metrics**: ROIC, ROE trends
+
+Create summary tables showing:
+```
+Historical Metrics (LTM):
+Revenue: $X million
+Revenue growth: X% CAGR
+Gross margin: X%
+EBIT margin: X%
+D&A % of revenue: X%
+CapEx % of revenue: X%
+FCF margin: X%
+```
+
+### Step 3: Build Revenue Projections
+
+**Methodology:**
+1. Start with latest actual revenue (LTM or most recent fiscal year)
+2. Apply growth rates for each projection year
+3. Show both dollar amounts AND calculated growth %
+
+**Growth Rate Framework:**
+- Year 1-2: Higher growth reflecting near-term visibility
+- Year 3-4: Gradual moderation toward industry average
+- Year 5+: Approaching terminal growth rate
+
+**Formula structure:**
+- Revenue(Year N) = Revenue(Year N-1) × (1 + Growth Rate)
+- Growth %(Year N) = Revenue(Year N) / Revenue(Year N-1) - 1
+
+**Three-scenario approach:**
+```
+Bear Case: Conservative growth (e.g., 8-12%)
+Base Case: Most likely scenario (e.g., 12-16%)
+Bull Case: Optimistic growth (e.g., 16-20%)
+```
+
+### Step 4: Operating Expense Modeling
+
+**Fixed/Variable Cost Analysis:**
+
+Operating expenses should model realistic operating leverage:
+- **Sales & Marketing**: Typically 15-40% of revenue depending on business model
+- **Research & Development**: Typically 10-30% for technology companies
+- **General & Administrative**: Typically 8-15% of revenue, shows leverage as company scales
+
+**Key principles:**
+- ALL percentages based on REVENUE, not gross profit
+- Model operating leverage: % should decline as revenue scales
+- Maintain separate line items for S&M, R&D, G&A
+- Calculate EBIT = Gross Profit - Total OpEx
+
+**Margin expansion framework:**
+```
+Current State → Target State (Year 5)
+Gross Margin: X% → Y% (justify based on scale, efficiency)
+EBIT Margin: X% → Y% (result of revenue growth + opex leverage)
+```
+
+### Step 5: Free Cash Flow Calculation
+
+**Build FCF in proper sequence:**
+
+```
+EBIT
+(-) Taxes (EBIT × Tax Rate)
+= NOPAT (Net Operating Profit After Tax)
+(+) D&A (non-cash expense, % of revenue)
+(-) CapEx (% of revenue, typically 4-8%)
+(-) Δ NWC (change in working capital)
+= Unlevered Free Cash Flow
+```
+
+**Working Capital Modeling:**
+- Calculate as % of revenue change (delta revenue)
+- Typical range: -2% to +2% of revenue change
+- Negative number = source of cash (working capital release)
+- Positive number = use of cash (working capital build)
+
+**Maintenance vs Growth CapEx:**
+- Maintenance CapEx: Sustains current operations (~2-3% revenue)
+- Growth CapEx: Supports expansion (additional 2-5% revenue)
+- Total CapEx should align with company's growth strategy
+
+### Step 6: Cost of Capital (WACC) Research
+
+**CAPM Methodology for Cost of Equity:**
+
+```
+Cost of Equity = Risk-Free Rate + Beta × Equity Risk Premium
+
+Where:
+- Risk-Free Rate = Current 10-Year Treasury Yield
+- Beta = 5-year monthly stock beta vs market index
+- Equity Risk Premium = 5.0-6.0% (market standard)
+```
+
+**Cost of Debt Calculation:**
+
+```
+After-Tax Cost of Debt = Pre-Tax Cost of Debt × (1 - Tax Rate)
+
+Determine Pre-Tax Cost of Debt from:
+- Credit rating (if available)
+- Current yield on company bonds
+- Interest expense / Total Debt from financials
+```
+
+**Capital Structure Weights:**
+
+```
+Market Value Equity = Current Stock Price × Shares Outstanding
+Net Debt = Total Debt - Cash & Equivalents
+Enterprise Value = Market Cap + Net Debt
+
+Equity Weight = Market Cap / Enterprise Value
+Debt Weight = Net Debt / Enterprise Value
+
+WACC = (Cost of Equity × Equity Weight) + (After-Tax Cost of Debt × Debt Weight)
+```
+
+**Special Cases:**
+- **Net Cash Position**: If Cash > Debt, Net Debt is NEGATIVE
+  - Debt Weight may be negative
+  - WACC calculation adjusts accordingly
+- **No Debt**: WACC = Cost of Equity
+
+**Typical WACC Ranges:**
+- Large Cap, Stable: 7-9%
+- Growth Companies: 9-12%
+- High Growth/Risk: 12-15%
+
+### Step 7: Discount Rate Application (5-10 Year Forecast)
+
+**Mid-Year Convention:**
+- Cash flows assumed to occur mid-year
+- Discount Period: 0.5, 1.5, 2.5, 3.5, 4.5, etc.
+- Discount Factor = 1 / (1 + WACC)^Period
+
+**Present Value Calculation:**
+```
+For each projection year:
+PV of FCF = Unlevered FCF × Discount Factor
+
+Example (Year 1):
+FCF = $1,000
+WACC = 10%
+Period = 0.5
+Discount Factor = 1 / (1.10)^0.5 = 0.9535
+PV = $1,000 × 0.9535 = $954
+```
+
+**Projection Period Selection:**
+- **5 years**: Standard for most analyses
+- **7-10 years**: High growth companies with longer runway
+- **3 years**: Mature, stable businesses
+
+### Step 8: Terminal Value Calculation
+
+**Perpetuity Growth Method (Preferred):**
+
+```
+Terminal FCF = Final Year FCF × (1 + Terminal Growth Rate)
+Terminal Value = Terminal FCF / (WACC - Terminal Growth Rate)
+
+Critical Constraint: Terminal Growth < WACC (otherwise infinite value)
+```
+
+**Terminal Growth Rate Selection:**
+- Conservative: 2.0-2.5% (GDP growth rate)
+- Moderate: 2.5-3.5%
+- Aggressive: 3.5-5.0% (only for market leaders)
+
+**Do not exceed**: Risk-free rate or long-term GDP growth
+
+**Exit Multiple Method (Alternative):**
+```
+Terminal Value = Final Year EBITDA × Exit Multiple
+
+Where Exit Multiple comes from:
+- Industry comparable trading multiples
+- Precedent transaction multiples
+- Typical range: 8-15x EBITDA
+```
+
+**Present Value of Terminal Value:**
+```
+PV of Terminal Value = Terminal Value / (1 + WACC)^Final Period
+
+Where Final Period accounts for timing:
+5-year model with mid-year convention: Period = 4.5
+```
+
+**Terminal Value Sanity Check:**
+- Should represent 50-70% of Enterprise Value
+- If >75%, model may be over-reliant on terminal assumptions
+- If <40%, check if terminal assumptions are too conservative
+
+### Step 9: Enterprise to Equity Value Bridge
+
+**Valuation Summary Structure:**
+
+```
+(+) Sum of PV of Projected FCFs = $X million
+(+) PV of Terminal Value = $Y million
+= Enterprise Value = $Z million
+
+(-) Net Debt [or + Net Cash if negative] = $A million
+= Equity Value = $B million
+
+÷ Diluted Shares Outstanding = C million shares
+= Implied Price per Share = $XX.XX
+
+Current Stock Price = $YY.YY
+Implied Return = (Implied Price / Current Price) - 1 = XX%
+```
+
+**Critical Adjustments:**
+- **Net Debt = Total Debt - Cash & Equivalents**
+  - If positive: Subtract from EV (reduces equity value)
+  - If negative (Net Cash): Add to EV (increases equity value)
+- **Use Diluted Shares**: Includes options, RSUs, convertible securities
+- **Other adjustments** (if applicable):
+  - Minority interests
+  - Pension liabilities
+  - Operating lease obligations
+
+**Valuation Output Format:**
+```csv
+Valuation Component,Amount ($M)
+PV Explicit FCFs,X.X
+PV Terminal Value,Y.Y
+Enterprise Value,Z.Z
+(-) Net Debt,A.A
+Equity Value,B.B
+,,
+Shares Outstanding (M),C.C
+Implied Price per Share,$XX.XX
+Current Share Price,$YY.YY
+Implied Upside/(Downside),+XX%
+```
+
+### Step 10: Sensitivity Analysis
+
+Build **three sensitivity tables** at the bottom of the DCF sheet showing how valuation changes with different assumptions:
+
+1. **WACC vs Terminal Growth** - Shows enterprise value sensitivity to discount rate and perpetuity growth
+2. **Revenue Growth vs EBIT Margin** - Shows impact of top-line growth and operating leverage
+3. **Beta vs Risk-Free Rate** - Shows sensitivity to cost of equity components
+
+**Implementation**: These are simple 2D grids (NOT Excel's "Data Table" feature) with formulas in each cell. Each cell must contain a full DCF recalculation for that specific assumption combination. See Critical Constraints section for detailed requirements on populating all 75 cells programmatically using openpyxl.
+
+<correct_patterns>
+
+This section contains all the CORRECT patterns to follow when building DCF models.
+
+### Scenario Block Selection Pattern - Follow This Approach
+
+**Assumptions are organized in separate blocks for each scenario:**
+
+**CRITICAL STRUCTURE - Three rows per section header:**
+
+```csv
+BEAR CASE ASSUMPTIONS (section header, merge cells across)
+Assumption,FY1,FY2,FY3,FY4,FY5
+Revenue Growth (%),12%,10%,9%,8%,7%
+EBIT Margin (%),45%,44%,43%,42%,41%
+
+BASE CASE ASSUMPTIONS (section header, merge cells across)
+Assumption,FY1,FY2,FY3,FY4,FY5
+Revenue Growth (%),16%,14%,12%,10%,9%
+EBIT Margin (%),48%,49%,50%,51%,52%
+
+BULL CASE ASSUMPTIONS (section header, merge cells across)
+Assumption,FY1,FY2,FY3,FY4,FY5
+Revenue Growth (%),20%,18%,15%,13%,11%
+EBIT Margin (%),50%,51%,52%,53%,54%
+```
+
+**Each scenario block MUST have a column header row** showing the projection years (FY2025E, FY2026E, etc.) immediately below the section title. Without this, users cannot tell which assumption value corresponds to which year.
+
+**How to reference assumptions - Create a consolidation column:**
+1. Case selector cell (e.g., B6) contains 1=Bear, 2=Base, or 3=Bull
+2. Create a consolidation column with INDEX or OFFSET formulas to pull from the correct scenario block
+3. Projection formulas reference the consolidation column (clean cell references)
+4. Each scenario block contains full set of DCF assumptions across projection years
+
+**Recommended consolidation column pattern (using INDEX):**
+`=INDEX(B10:D10, 1, $B$6)`
+
+**NOT this - scattered IF statements throughout:**
+`=IF($B$6=1,[Bear block cell],IF($B$6=2,[Base block cell],[Bull block cell]))`
+
+The consolidation column approach centralizes logic and makes the model easier to audit.
+
+### Correct Revenue Projection Pattern
+
+**Create a consolidation column with INDEX formulas, then reference it in projections:**
+
+**Step 1 - Consolidation column for FY1 growth:**
+`=INDEX([Bear FY1 growth]:[Bull FY1 growth], 1, $B$6)`
+
+**Step 2 - Revenue projection references the consolidation column:**
+`Revenue Year 1: =D29*(1+$E$10)`
+
+Where:
+- D29 = Prior year revenue
+- $E$10 = Consolidation column cell for FY1 growth (contains INDEX formula)
+- $B$6 = Case selector (1=Bear, 2=Base, 3=Bull)
+
+**This approach is cleaner than embedding IF statements in every projection formula** and makes it much easier to audit which scenario assumptions are being used.
+
+### Correct FCF Formula Pattern
+
+**Use consolidation columns with INDEX formulas, then reference them in FCF calculations:**
+
+**Consolidation column approach:**
+```csv
+Item,Formula,Reference
+D&A,=E29*$E$21,$E$21 = consolidation column for D&A %
+CapEx,=E29*$E$22,$E$22 = consolidation column for CapEx %
+Δ NWC,=(E29-D29)*$E$23,$E$23 = consolidation column for NWC %
+Unlevered FCF,=E57+E58-E60-E62,E57=NOPAT E58=D&A E60=CapEx E62=Δ NWC
+```
+
+**Each consolidation column cell contains an INDEX formula** that pulls from the appropriate scenario block based on case selector. This keeps projection formulas clean and auditable.
+
+Before writing formulas, confirm scenario block row locations and set up consolidation columns.
+
+### Correct Cell Comment Format
+
+**Every hardcoded value needs this format:**
+
+"Source: [System/Document], [Date], [Reference], [URL if applicable]"
+
+**Examples:**
+```csv
+Item,Source Comment
+Stock price,Source: Market data script 2025-10-12 Close price
+Shares outstanding,Source: 10-K FY2024 Page 45 Note 12
+Historical revenue,Source: 10-K FY2024 Page 32 Consolidated Statements
+Beta,Source: Market data script 2025-10-12 5-year monthly beta
+Consensus estimates,Source: Management guidance Q3 2024 earnings call
+```
+
+### Correct Assumption Table Structure
+
+**CRITICAL: Each scenario block requires THREE structural elements:**
+
+1. **Section header row** (merged cells): e.g., "BEAR CASE ASSUMPTIONS"
+2. **Column header row** showing years - THIS IS REQUIRED, DO NOT SKIP
+3. **Data rows** with assumption values
+
+**Structure:**
+```csv
+BEAR CASE ASSUMPTIONS (section header - merge across columns A:G)
+Assumption,FY1,FY2,FY3,FY4,FY5
+Revenue Growth (%),X%,X%,X%,X%,X%
+EBIT Margin (%),X%,X%,X%,X%,X%
+Terminal Growth,X%,,,,
+WACC,X%,,,,
+
+BASE CASE ASSUMPTIONS (section header - merge across columns A:G)
+Assumption,FY1,FY2,FY3,FY4,FY5
+Revenue Growth (%),X%,X%,X%,X%,X%
+EBIT Margin (%),X%,X%,X%,X%,X%
+Terminal Growth,X%,,,,
+WACC,X%,,,,
+
+BULL CASE ASSUMPTIONS (section header - merge across columns A:G)
+Assumption,FY1,FY2,FY3,FY4,FY5
+Revenue Growth (%),X%,X%,X%,X%,X%
+EBIT Margin (%),X%,X%,X%,X%,X%
+Terminal Growth,X%,,,,
+WACC,X%,,,,
+```
+
+**WITHOUT the column header row showing projection years (FY2025E, FY2026E, etc.), users cannot tell which assumption value corresponds to which year. This row is MANDATORY.**
+
+**Then create a consolidation column** (typically the next column to the right) that uses INDEX formulas to pull from the selected scenario block based on the case selector. This consolidation column is what your projection formulas reference.
+
+### Correct Row Planning Process
+
+**1. Write ALL headers and labels FIRST:**
+```csv
+Row,Content
+1,[Company Name] DCF Model
+2,Ticker | Date | Year End
+4,Case Selector
+7,KEY ASSUMPTIONS
+26,Assumption headers
+27-31,Growth assumptions
+...,...
+```
+
+**2. Write ALL section dividers and blank rows**
+
+**3. THEN write formulas using the locked row positions**
+
+**4. Test formulas immediately after creation**
+
+**Think of it like construction:**
+- Good: Pour foundation, then build walls (stable structure)
+- Bad: Build walls, then pour foundation (walls collapse)
+
+**Excel version:**
+- Good: Add headers, then write formulas (formulas stable)
+- Bad: Write formulas, then add headers (formulas break)
+
+### Correct Sensitivity Table Implementation
+
+**IMPORTANT**: These are NOT Excel's "Data Table" feature. These are simple grids where you write regular formulas using openpyxl. Yes, this means ~75 formulas total (3 tables × 25 cells each), but this is straightforward and required.
+
+**Programmatic Population with Formulas:**
+
+Each sensitivity table must be fully populated with formulas that recalculate the implied share price for each combination of assumptions. **Do not use Excel's Data Table feature** (it requires manual intervention and cannot be automated via openpyxl).
+
+**Implementation approach - CONCRETE EXAMPLE:**
+
+**Table Structure — 5×5 grid (ODD dimensions, base case centered):**
+
+If the model's base WACC = 9.0% and base terminal growth = 3.0%, build the axes symmetrically around those values:
+
+```csv
+WACC vs Terminal Growth,  2.0%,  2.5%,  3.0%,  3.5%,  4.0%
+              8.0%,       [fml], [fml], [fml], [fml], [fml]
+              8.5%,       [fml], [fml], [fml], [fml], [fml]
+              9.0%,       [fml], [fml], [★  ], [fml], [fml]   ← middle row = base WACC
+              9.5%,       [fml], [fml], [fml], [fml], [fml]
+             10.0%,       [fml], [fml], [fml], [fml], [fml]
+                                   ↑
+                          middle col = base terminal g
+```
+
+**★ = the center cell.** Its formula output MUST equal the model's actual implied share price (from the valuation summary). Apply the medium-blue fill (`#BDD7EE`) and bold font to this cell so the base case is visually anchored.
+
+**Rule for axis values:** `axis_values = [base - 2*step, base - step, base, base + step, base + 2*step]` — symmetric around the base, odd count guarantees a center.
+
+**Formula Pattern - Cell B88 (WACC=8.0%, Terminal Growth=2.0%):**
+
+The formula in B88 should recalculate the implied price using:
+- WACC from row header: `$A88` (8.0%)
+- Terminal Growth from column header: `B$87` (2.0%)
+
+**Recommended approach:** Reference the main DCF calculation but substitute these values.
+
+**Example formula structure:**
+`=([SUM of PV FCFs using $A88 as discount rate] + [Terminal Value using B$87 as growth rate and $A88 as WACC] - [Net Debt]) / [Shares]`
+
+**CRITICAL - Write a formula for EVERY cell in the 5x5 grid (25 cells per table, 75 cells total).** Use openpyxl to write these formulas programmatically in a loop. Do NOT skip this step or leave placeholder text.
+
+**Python implementation pattern:**
+```python
+# Pseudocode for populating sensitivity table
+for row_idx, wacc_value in enumerate(wacc_range):
+    for col_idx, term_growth_value in enumerate(term_growth_range):
+        # Build formula that uses wacc_value and term_growth_value
+        formula = f"=<DCF recalc using {wacc_value} and {term_growth_value}>"
+        ws.cell(row=start_row+row_idx, column=start_col+col_idx).value = formula
+```
+
+**The sensitivity tables must work immediately when the model is opened, with no manual steps required from the user.**
+
+</correct_patterns>
+
+<common_mistakes>
+
+This section contains all the WRONG patterns to avoid when building DCF models.
+
+### WRONG: Simplified Sensitivity Table Approximations or Placeholder Text
+
+**Don't use linear approximations:**
+
+```
+// WRONG - Linear approximation
+B97: =B88*(1+(0.096-0.116))    // Assumes linear relationship
+
+// WRONG - Division shortcut
+B105: =B88/(1+(E48-0.07))      // Doesn't recalculate full DCF
+```
+
+**Don't leave placeholder text:**
+```
+// WRONG - Placeholder note
+"Note: Use Excel Data Table feature (Data → What-If Analysis → Data Table) to populate sensitivity tables."
+
+// WRONG - Empty cells
+[leaving cells blank because "this is complex"]
+```
+
+**Don't confuse terminology:**
+- ❌ "Sensitivity tables need Excel's Data Table feature" (NO - that's a specific Excel tool we can't use)
+- ✅ "Sensitivity tables are simple grids with formulas in each cell" (YES - this is what we build)
+
+**Why these shortcuts are wrong:**
+- Linear approximation formulas don't actually recalculate the DCF - they just apply simple math adjustments
+- The relationships are not linear, so the results will be inaccurate
+- Placeholder text requires manual user intervention
+- Model is not immediately usable when delivered
+- Not professional or client-ready
+- Empty cells = incomplete deliverable
+
+**Common rationalization to REJECT:**
+"Writing 75+ formulas feels complex, so I'll leave a note for the user to complete it manually."
+
+**Reality:** Writing 75 formulas is straightforward when you use a loop in Python with openpyxl. Each formula follows the same pattern - just substitute the row/column values. This is a required part of the deliverable.
+
+**Instead:** Populate every sensitivity cell with formulas that recalculate the full DCF for that specific combination of assumptions
+
+### WRONG: Missing Cell Comments
+
+**Don't do this:**
+- Create all hardcoded inputs without comments
+- Think "I'll add them later"
+- Write "TODO: add source"
+- Leave blue inputs without documentation
+
+**Why it's wrong:**
+- Can't verify where data came from
+- Fails xlsx skill requirements
+- Not audit-ready
+- Wastes time fixing later
+
+**Instead:** Add cell comment AS EACH hardcoded value is created
+
+### WRONG: Formula Row References Off
+
+**Symptom:**
+The FCF section references wrong assumption rows:
+`D&A:  =E29*$E$34    // Should be $E$21, but referencing wrong row`
+`CapEx: =E29*$E$41   // Should be $E$22, but row shifted`
+
+**Why this happens:**
+1. Formulas written first
+2. Then headers inserted
+3. All row references shifted
+4. Now formulas point to wrong cells → #REF! errors
+
+**Instead:** Lock row layout FIRST, then write formulas
+
+### WRONG: Single Row for Each Assumption Across Scenarios
+
+**Don't structure assumptions like this:**
+```csv
+Assumption,Bear,Base,Bull
+Revenue Growth FY1,10%,13%,16%
+Revenue Growth FY2,9%,12%,15%
+```
+This vertical layout makes it hard to see the progression across years within each scenario.
+
+**Why it's wrong:**
+- Makes it difficult to see assumptions evolving across years within each scenario
+- Harder to compare scenario assumptions across full projection period
+- Less intuitive for reviewing scenario logic
+
+**Instead:**
+- Create separate blocks for each scenario (Bear, Base, Bull)
+- Within each block, show assumptions horizontally across projection years
+- This makes each scenario's assumptions easier to review as a cohesive set
+
+### WRONG: No Borders
+
+**Don't deliver a model without borders:**
+- No section delineation
+- All cells blend together
+- Hard to read and unprofessional
+
+**Why it's wrong:**
+- Not client-ready
+- Difficult to navigate
+- Looks amateur
+
+**Instead:** Add borders around all major sections
+
+### WRONG: Wrong Font Colors or No Font Color Distinction
+
+**Don't do this:**
+- All text is black
+- Only use fill colors (no font color changes)
+- Mix up which cells are blue vs black
+
+**Why it's wrong:**
+- Can't distinguish inputs from formulas
+- Auditing becomes impossible
+- Violates xlsx skill requirements
+
+**Instead:** Blue text for ALL hardcoded inputs, black text for ALL formulas, green for sheet links
+
+### WRONG: Operating Expenses Based on Gross Profit
+
+**Don't do this:**
+`S&M: =E33*0.15    // E33 = Gross Profit (WRONG)`
+
+**Why it's wrong:**
+- Operating expenses scale with revenue, not gross profit
+- Produces unrealistic margin progression
+- Not how businesses actually operate
+
+**Instead:**
+`S&M: =E29*0.15    // E29 = Revenue (CORRECT)`
+
+### TOP 5 ERRORS SUMMARY
+
+1. **Formula row references off** → Define ALL row positions BEFORE writing formulas
+2. **Missing cell comments** → Add comments AS cells are created, not at end
+3. **Simplified sensitivity tables** → Populate all cells with full DCF recalc formulas, not approximations
+4. **Scenario block references wrong** → Ensure IF formulas pull from correct Bear/Base/Bull blocks
+5. **No borders** → Add professional section borders for client-ready appearance
+
+In addition, be aware of these errors:
+
+### WACC Calculation Errors
+- Mixing book and market values in capital structure
+- Using equity beta instead of asset/unlevered beta incorrectly
+- Wrong tax rate application to cost of debt
+- Incorrect risk-free rate (must use current 10Y Treasury)
+- Failure to adjust for net debt vs net cash position
+
+### Growth Assumption Flaws
+- Terminal growth > WACC (creates infinite value)
+- Projection growth rates inconsistent with historical performance
+- Ignoring industry growth constraints
+- Revenue growth not aligned with unit economics
+- Margin expansion without operational justification
+
+### Terminal Value Mistakes
+- Using wrong growth method (perpetuity vs exit multiple)
+- Terminal value >80% of enterprise value (suggests over-reliance)
+- Inconsistent terminal margins with steady state assumptions
+- Wrong discount period for terminal value
+
+### Cash Flow Projection Errors
+- Operating expenses based on gross profit instead of revenue
+- D&A/CapEx percentages misaligned with business model
+- Working capital changes not properly calculated
+- Tax rate inconsistency between years
+- NOPAT calculation errors
+
+**These errors are the most common. Re-read this section before starting any DCF build.**
+
+</common_mistakes>
+
+## Excel File Creation
+
+**This skill uses the `xlsx` skill for all spreadsheet operations.** The xlsx skill provides:
+- Standardized formula construction rules
+- Number formatting conventions
+- Automated formula recalculation via `recalc.py` script
+- Comprehensive error checking and validation
+
+All Excel files created by this skill must follow xlsx skill requirements, including zero formula errors and proper recalculation.
+
+## Quality Rubric
+
+Every DCF model must maximize for:
+1. **Realistic revenue and margin assumptions** based on historical performance
+2. **Appropriate cost of capital calculation** with proper CAPM methodology
+3. **Comprehensive sensitivity analysis** showing valuation ranges
+4. **Clear terminal value calculation** with supporting rationale
+5. **Professional model structure** enabling scenario analysis
+6. **Transparent documentation** of all key assumptions
+
+## Input Requirements
+
+### Minimum Required Inputs
+1. **Company identifier**: Ticker symbol or company name
+2. **Growth assumptions**: Revenue growth rates for projection period (or "use consensus")
+3. **Optional parameters**:
+   - Projection period (default: 5 years)
+   - Scenario cases (Bear/Base/Bull growth and margin assumptions)
+   - Terminal growth rate (default: 2.5-3.0%)
+   - Specific WACC inputs if not using CAPM
+
+## Excel Model Structure
+
+### Sheet Architecture
+
+Create **two sheets**:
+
+1. **DCF** - Main valuation model with sensitivity analysis at bottom
+2. **WACC** - Cost of capital calculation
+
+**CRITICAL**: Sensitivity tables go at the BOTTOM of the DCF sheet (not on a separate sheet). This keeps all valuation outputs together.
+
+### Formula Recalculation (MANDATORY)
+
+After creating or modifying the Excel model, **recalculate all formulas** using the `recalc.py` script from the `excel-author` skill:
+
+```bash
+python recalc.py [path_to_excel_file] [timeout_seconds]
+```
+
+Example:
+```bash
+python recalc.py AAPL_DCF_Model_2025-10-12.xlsx 30
+```
+
+The script will:
+- Recalculate all formulas in all sheets using LibreOffice
+- Scan ALL cells for Excel errors (#REF!, #DIV/0!, #VALUE!, #NAME?, #NULL!, #NUM!, #N/A)
+- Return detailed JSON with error locations and counts
+
+**Expected output format:**
+```json
+{
+  "status": "success",           // or "errors_found"
+  "total_errors": 0,              // Total error count
+  "total_formulas": 42,           // Number of formulas in file
+  "error_summary": {}             // Only present if errors found
+}
+```
+
+**If errors are found**, the output will include details:
+```json
+{
+  "status": "errors_found",
+  "total_errors": 2,
+  "total_formulas": 42,
+  "error_summary": {
+    "#REF!": {
+      "count": 2,
+      "locations": ["DCF!B25", "DCF!C25"]
+    }
+  }
+}
+```
+
+**Fix all errors** and re-run recalc.py until status is "success" before delivering the model.
+
+### Formatting Standards
+
+**IMPORTANT**: Follow the xlsx skill for formula construction rules and number formatting conventions. The DCF skill adds specific visual presentation standards.
+
+**Color Scheme - Two Layers**:
+
+**Layer 1: Font Colors (MANDATORY from xlsx skill)**
+- **Blue text (RGB: 0,0,255)**: ALL hardcoded inputs (stock price, shares, historical data, assumptions)
+- **Black text (RGB: 0,0,0)**: ALL formulas and calculations
+- **Green text (RGB: 0,128,0)**: Links to other sheets (WACC sheet references)
+
+**Layer 2: Fill Colors — Professional Blue/Grey Palette (Default unless user specifies otherwise)**
+- **Keep it minimal** — use only blues and greys for fills. Do NOT introduce greens, yellows, oranges, or multiple accent colors. A model with too many colors looks amateurish.
+- **Default fill palette:**
+  - **Section headers**: Dark blue (RGB: 31,78,121 / `#1F4E79`) background with white bold text
+  - **Sub-headers/column headers**: Light blue (RGB: 217,225,242 / `#D9E1F2`) background with black bold text
+  - **Input cells**: Light grey (RGB: 242,242,242 / `#F2F2F2`) background with blue font — or just white with blue font if you want maximum minimalism
+  - **Calculated cells**: White background with black font
+  - **Output/summary rows** (per-share value, EV, etc.): Medium blue (RGB: 189,215,238 / `#BDD7EE`) background with black bold font
+- **That's it — 3 blues + 1 grey + white.** Resist the urge to add more.
+- User-provided templates or explicit color preferences ALWAYS override these defaults.
+
+**How the layers work together:**
+- Input cell: Blue font + light grey fill = "Hardcoded input"
+- Formula cell: Black font + white background = "Calculated value"
+- Sheet link: Green font + white background = "Reference from another sheet"
+- Key output: Black bold font + medium blue fill = "This is the answer"
+
+**Font color tells you WHAT it is (input/formula/link). Fill color tells you WHERE you are (header/data/output).**
+
+### Border Standards (REQUIRED for Professional Appearance)
+
+**Thick borders** (1.5pt) around major sections:
+- KEY INPUTS section
+- PROJECTION ASSUMPTIONS section
+- 5-YEAR CASH FLOW PROJECTION section
+- TERMINAL VALUE section
+- VALUATION SUMMARY section
+- Each SENSITIVITY ANALYSIS table
+
+**Medium borders** (1pt) between sub-sections:
+- Company Details vs Historical Performance
+- Growth Assumptions vs EBIT Margin vs FCF Parameters
+
+**Thin borders** (0.5pt) around data tables:
+- Scenario assumption tables (Bear | Base | Bull | Selected)
+- Historical vs projected financials matrix
+
+**No borders:** Individual cells within tables (keep clean, scannable)
+
+**Borders are mandatory** - models without professional borders are not client-ready.
+
+**Number Formats** (follows xlsx skill standards):
+- **Years**: Format as text strings (e.g., "2024" not "2,024")
+- **Percentages**: `0.0%` (one decimal place)
+- **Currency**: `$#,##0` for millions; `$#,##0.00` for per-share - ALWAYS specify units in headers ("Revenue ($mm)")
+- **Zeros**: Use number formatting to make all zeros "-" (e.g., `$#,##0;($#,##0);-`)
+- **Large numbers**: `#,##0` with thousands separator
+- **Negative numbers**: `(#,##0)` in parentheses (NOT minus sign)
+
+**Cell Comments (MANDATORY for all hardcoded inputs)**:
+
+Per the xlsx skill, ALL hardcoded values must have cell comments documenting the source. Format: "Source: [System/Document], [Date], [Reference], [URL if applicable]"
+
+**CRITICAL**: Add comments AS CELLS ARE CREATED. Do not defer to the end.
+
+### DCF Sheet Detailed Structure
+
+**Section 1: Header**
+```csv
+Row,Content
+1,[Company Name] DCF Model
+2,Ticker: [XXX] | Date: [Date] | Year End: [FYE]
+3,Blank
+4,Case Selector Cell (1=Bear 2=Base 3=Bull)
+5,Case Name Display (formula: =IF([Selector]=1"Bear"IF([Selector]=2"Base""Bull")))
+```
+
+**Section 2: Market Data (NOT case dependent)**
+```csv
+Item,Value
+Current Stock Price,$XX.XX
+Shares Outstanding (M),XX.X
+Market Cap ($M),[Formula]
+Net Debt ($M),XXX [or Net Cash if negative]
+```
+
+**Section 3: DCF Scenario Assumptions**
+
+Create separate assumption blocks for each scenario (Bear, Base, Bull) with DCF-specific assumptions (Revenue Growth %, EBIT Margin %, Tax Rate %, D&A % of Revenue, CapEx % of Revenue, NWC Change % of ΔRev, Terminal Growth Rate, WACC) laid out horizontally across projection years. Each block must include section header, column header row showing the projection years (FY1, FY2, etc.), and data rows. See `<correct_patterns>` section "Correct Assumption Table Structure" for the exact layout.
+
+**Section 4: Historical & Projected Financials**
+
+**Reference a consolidation column (e.g., "Selected Case") that pulls from scenario blocks**, not scattered IF formulas in every projection row.
+
+```csv
+Income Statement ($M),2020A,2021A,2022A,2023A,2024E,2025E,2026E
+Revenue,XXX,XXX,XXX,XXX,[=E29*(1+$E$10)],[=F29*(1+$E$11)],[=G29*(1+$E$12)]
+  % growth,XX%,XX%,XX%,XX%,[=E29/D29-1],[=F29/E29-1],[=G29/F29-1]
+,,,,,,
+Gross Profit,XXX,XXX,XXX,XXX,[=E29*E33],[=F29*F33],[=G29*G33]
+  % margin,XX%,XX%,XX%,XX%,[=E33/E29],[=F33/F29],[=G33/G29]
+,,,,,,
+Operating Expenses:,,,,,,,
+  S&M,XXX,XXX,XXX,XXX,[=E29*0.15],[=F29*0.14],[=G29*0.13]
+  R&D,XXX,XXX,XXX,XXX,[=E29*0.12],[=F29*0.11],[=G29*0.10]
+  G&A,XXX,XXX,XXX,XXX,[=E29*0.08],[=F29*0.07],[=G29*0.07]
+  Total OpEx,XXX,XXX,XXX,XXX,[=E36+E37+E38],[=F36+F37+F38],[=G36+G37+G38]
+,,,,,,
+EBIT,XXX,XXX,XXX,XXX,[=E33-E39],[=F33-F39],[=G33-G39]
+  % margin,XX%,XX%,XX%,XX%,[=E41/E29],[=F41/F29],[=G41/G29]
+,,,,,,
+Taxes,(XX),(XX),(XX),(XX),[=E41*$E$24],[=F41*$E$24],[=G41*$E$24]
+  Tax rate,XX%,XX%,XX%,XX%,[=E43/E41],[=F43/F41],[=G43/G41]
+,,,,,,
+NOPAT,XXX,XXX,XXX,XXX,[=E41-E43],[=F41-F43],[=G41-G43]
+```
+
+**Key Formula Pattern**:
+- Revenue growth: `=E29*(1+$E$10)` where $E$10 is consolidation column for Year 1 growth
+- NOT: `=E29*(1+IF($B$6=1,$B$10,IF($B$6=2,$C$10,$D$10)))`
+
+This approach is cleaner, easier to audit, and prevents formula errors by centralizing the scenario logic.
+
+**Section 5: Free Cash Flow Build**
+
+**CRITICAL**: Verify row references point to the CORRECT assumption rows. Test formulas immediately after creation.
+
+```csv
+Cash Flow ($M),2020A,2021A,2022A,2023A,2024E,2025E,2026E
+NOPAT,XXX,XXX,XXX,XXX,[=E45],[=F45],[=G45]
+(+) D&A,XXX,XXX,XXX,XXX,[=E29*$E$21],[=F29*$E$21],[=G29*$E$21]
+    % of Rev,XX%,XX%,XX%,XX%,[=E58/E29],[=F58/F29],[=G58/G29]
+(-) CapEx,(XX),(XX),(XX),(XX),[=E29*$E$22],[=F29*$E$22],[=G29*$E$22]
+    % of Rev,XX%,XX%,XX%,XX%,[=E60/E29],[=F60/F29],[=G60/G29]
+(-) Δ NWC,(XX),(XX),(XX),(XX),[=(E29-D29)*$E$23],[=(F29-E29)*$E$23],[=(G29-F29)*$E$23]
+    % of Δ Rev,XX%,XX%,XX%,XX%,[=E62/(E29-D29)],[=F62/(F29-E29)],[=G62/(G29-F29)]
+,,,,,,
+Unlevered FCF,XXX,XXX,XXX,XXX,[=E57+E58-E60-E62],[=F57+F58-F60-F62],[=G57+G58-G60-G62]
+```
+
+**Row reference examples** (based on layout planning):
+- $E$21 = D&A % assumption (consolidation column, row 21)
+- $E$22 = CapEx % assumption (consolidation column, row 22)
+- $E$23 = NWC % assumption (consolidation column, row 23)
+- E29 = Revenue for year (row 29)
+- E45 = NOPAT for year (row 45)
+
+**Before writing formulas**: Confirm these row numbers match the actual layout. Test one column, then copy across.
+
+**Section 6: Discounting & Valuation**
+```csv
+DCF Valuation,2024E,2025E,2026E,2027E,2028E,Terminal
+Unlevered FCF ($M),XXX,XXX,XXX,XXX,XXX,
+Period,0.5,1.5,2.5,3.5,4.5,
+Discount Factor,0.XX,0.XX,0.XX,0.XX,0.XX,
+PV of FCF ($M),XXX,XXX,XXX,XXX,XXX,
+,,,,,,
+Terminal FCF ($M),,,,,,,XXX
+Terminal Value ($M),,,,,,,XXX
+PV Terminal Value ($M),,,,,,,XXX
+,,,,,,
+Valuation Summary ($M),,,,,,
+Sum of PV FCFs,XXX,,,,,
+PV Terminal Value,XXX,,,,,
+Enterprise Value,XXX,,,,,
+(-) Net Debt,(XX),,,,,
+Equity Value,XXX,,,,,
+,,,,,,
+Shares Outstanding (M),XX.X,,,,,
+IMPLIED PRICE PER SHARE,$XX.XX,,,,,
+Current Stock Price,$XX.XX,,,,,
+Implied Upside/(Downside),XX%,,,,,
+```
+
+### WACC Sheet Structure
+
+```csv
+COST OF EQUITY CALCULATION,,
+Risk-Free Rate (10Y Treasury),X.XX%,[Yellow input]
+Beta (5Y monthly),X.XX,[Yellow input]
+Equity Risk Premium,X.XX%,[Yellow input]
+Cost of Equity,X.XX%,[Calculated blue]
+,,
+COST OF DEBT CALCULATION,,
+Credit Rating,AA-,[Yellow input]
+Pre-Tax Cost of Debt,X.XX%,[Yellow input]
+Tax Rate,XX.X%,[Link to DCF sheet]
+After-Tax Cost of Debt,X.XX%,[Calculated blue]
+,,
+CAPITAL STRUCTURE,,
+Current Stock Price,$XX.XX,[Link to DCF]
+Shares Outstanding (M),XX.X,[Link to DCF]
+Market Capitalization ($M),"X,XXX",[Calculated]
+,,
+Total Debt ($M),XXX,[Yellow input]
+Cash & Equivalents ($M),XXX,[Yellow input]
+Net Debt ($M),XXX,[Calculated]
+,,
+Enterprise Value ($M),"X,XXX",[Calculated]
+,,
+WACC CALCULATION,Weight,Cost,Contribution
+Equity,XX.X%,X.X%,X.XX%
+Debt,XX.X%,X.X%,X.XX%
+,,
+WEIGHTED AVERAGE COST OF CAPITAL,X.XX%,[Green output]
+```
+
+**Key WACC Formulas:**
+```
+Market Cap = Price × Shares
+Net Debt = Total Debt - Cash
+Enterprise Value = Market Cap + Net Debt
+Equity Weight = Market Cap / EV
+Debt Weight = Net Debt / EV
+WACC = (Cost of Equity × Equity Weight) + (After-tax Cost of Debt × Debt Weight)
+```
+
+### Sensitivity Analysis (Bottom of DCF Sheet)
+
+**TERMINOLOGY REMINDER**: "Sensitivity tables" = simple 2D grids with row headers, column headers, and formulas in each data cell. NOT Excel's "Data Table" feature (Data → What-If Analysis → Data Table). You will use openpyxl to write regular Excel formulas into each cell.
+
+**Location**: Rows 87+ on DCF sheet (NOT a separate sheet)
+
+**Three sensitivity tables, vertically stacked:**
+
+1. **WACC vs Terminal Growth** (rows 87-100) - 5x5 grid = 25 cells with formulas
+2. **Revenue Growth vs EBIT Margin** (rows 102-115) - 5x5 grid = 25 cells with formulas
+3. **Beta vs Risk-Free Rate** (rows 117-130) - 5x5 grid = 25 cells with formulas
+
+**Total formulas to write: 75** (this is required, not optional)
+
+**CRITICAL**: All sensitivity table cells must be populated programmatically with formulas using openpyxl. DO NOT use linear approximation shortcuts. DO NOT leave placeholder text or notes about manual steps. DO NOT rationalize leaving cells empty because "it's complex" - use a Python loop to generate the formulas.
+
+**Table Setup:**
+1. Create table structure with row/column headers (the assumption values to test)
+2. Populate EVERY data cell with a formula that:
+   - Uses the row header value (e.g., WACC = 9.0%)
+   - Uses the column header value (e.g., Terminal Growth = 3.0%)
+   - Recalculates the full DCF with those specific assumptions
+   - Returns the implied share price for that scenario
+3. All cells must contain working formulas when delivered
+4. Format cells with conditional formatting: Green scale for higher values, red scale for lower values
+5. Bold the base case cell
+6. Leave 1-2 blank rows between tables
+
+**No manual intervention required** - the sensitivity tables must be fully functional when the user opens the file.
+
+## Case Selector Implementation
+
+**Three-Case Framework:**
+
+### Bear Case
+- Conservative revenue growth (low end of historical range)
+- Margin compression or no expansion
+- Higher WACC (risk premium increase)
+- Lower terminal growth rate
+- Higher CapEx assumptions
+
+### Base Case
+- Consensus or management guidance revenue growth
+- Moderate margin expansion based on operating leverage
+- Current market-implied WACC
+- GDP-aligned terminal growth (2.5-3.0%)
+- Standard CapEx assumptions
+
+### Bull Case
+- Optimistic revenue growth (high end of projections)
+- Significant margin expansion
+- Lower WACC (reduced risk premium)
+- Higher terminal growth (3.5-5.0%)
+- Reduced CapEx intensity
+
+**Formula Implementation:**
+
+**DO NOT use nested IF formulas scattered throughout.** Instead, create a consolidation column that uses INDEX or OFFSET formulas to pull from the appropriate scenario block.
+
+**Recommended pattern (using INDEX):**
+`=INDEX(B10:D10, 1, $B$6)` where `B10:D10` = Bear/Base/Bull values, `1` = row offset, `$B$6` = case selector cell (1, 2, or 3)
+
+**Then reference the consolidation column** in all projections:
+`Revenue Year 1: =D29*(1+$E$10)` where $E$10 is the consolidation column value for Year 1 growth.
+
+This approach centralizes scenario logic, making the model easier to audit and maintain.
+
+## Deliverables Structure
+
+**File naming**: `[Ticker]_DCF_Model_[Date].xlsx`
+
+**Two sheets**:
+1. **DCF** - Complete model with Bear/Base/Bull cases + three sensitivity tables at bottom (WACC vs Terminal Growth, Revenue Growth vs EBIT Margin, Beta vs Risk-Free Rate)
+2. **WACC** - Cost of capital calculation
+
+**Key features**: Case selector (1/2/3), consolidation column with INDEX/OFFSET formulas, color-coded cells, cell comments on all inputs, professional borders
+
+## Best Practices
+
+### Model Construction
+1. **Build incrementally**: Complete each section before moving to next
+2. **Test as building**: Enter sample numbers to verify formulas
+3. **Use consistent structure**: Similar calculations follow similar patterns
+4. **Comment complex formulas**: Add notes for unusual calculations
+5. **Build in checks**: Sum checks and balance checks where applicable
+
+### Documentation
+1. **Document all assumptions**: Explain reasoning behind key inputs
+2. **Cite data sources**: Note where each data point came from
+3. **Explain methodology**: Describe any non-standard approaches
+4. **Flag uncertainties**: Highlight areas with limited visibility
+
+### Quality Control
+1. **Cross-check calculations**: Verify math in multiple ways
+2. **Stress test assumptions**: Run sensitivity to ensure model is robust
+3. **Peer review**: Have someone else check formulas
+4. **Version control**: Save versions as work progresses
+
+## Common Variations
+
+### High-Growth Technology Companies
+- Longer projection period (7-10 years)
+- Higher initial growth rates (20-30%)
+- Significant margin expansion over time
+- Higher WACC (12-15%)
+- Model unit economics (users, ARPU, etc.)
+
+### Mature/Stable Companies
+- Shorter projection period (3-5 years)
+- Modest growth rates (GDP +1-3%)
+- Stable margins
+- Lower WACC (7-9%)
+- Focus on cash generation and capital allocation
+
+### Cyclical Companies
+- Model through economic cycle
+- Normalize margins at mid-cycle
+- Consider trough and peak scenarios
+- Adjust beta for cyclicality
+
+### Multi-Segment Companies
+- Separate DCFs for each business unit
+- Different growth rates and margins by segment
+- Sum-of-parts valuation
+- Consider synergies
+
+## Troubleshooting
+
+**If you encounter errors or unreasonable results, read [TROUBLESHOOTING.md](./TROUBLESHOOTING.md) for detailed debugging guidance.**
+
+## Workflow Integration
+
+### At Start of DCF Build
+
+1. **Gather market data**:
+   - Check for available MCP servers for current market data
+   - Use web search/fetch for stock prices, beta, and other market metrics
+   - Request from user if specific data is needed
+
+2. **Gather historical financials**:
+   - Check for available MCP servers (Daloopa, etc.)
+   - Request from user if not available via MCP
+   - Manual extraction from 10-Ks if necessary
+
+3. **Begin model construction** using the DCF methodology detailed in this skill
+
+### During Model Construction
+
+1. **Build Excel model** using openpyxl with formulas (not hardcoded values)
+2. **Follow xlsx skill conventions** for formula construction and formatting
+3. **Apply fill colors only if requested** by user or if specific brand guidelines are provided
+
+### Before Delivering Model (MANDATORY)
+
+1. **Verify structure**:
+   - Scenario blocks for Bear/Base/Bull with assumptions across projection years
+   - Case selector functional with formulas referencing correct scenario blocks
+   - Sensitivity tables at bottom of DCF sheet (not separate sheet)
+   - Font colors: Blue inputs, black formulas, green sheet links
+   - Cell comments on ALL hardcoded inputs
+   - Professional borders around major sections
+
+2. **Recalculate formulas**: Run `python recalc.py model.xlsx 30`
+
+3. **Check output**:
+   - If `status` is `"success"` → Continue to step 4
+   - If `status` is `"errors_found"` → Check `error_summary` and read [TROUBLESHOOTING.md](./TROUBLESHOOTING.md) for debugging guidance
+
+4. **Fix errors and re-run recalc.py** until status is "success"
+
+5. **Spot-check formulas**:
+   - Test one FCF formula - does it reference the correct assumption rows?
+   - Change case selector - does the consolidation column update properly?
+   - Verify revenue formulas reference consolidation column (not nested IF formulas)
+
+6. **Deliver model**
+
+### Available Data Sources
+
+- **MCP servers**: If configured (Daloopa for historical financials)
+- **Web search/fetch**: For current stock prices, beta, and market data
+- **User-provided data**: Historical financials, consensus estimates
+- **Manual extraction**: SEC EDGAR filings as fallback
+
+## Final Output Checklist
+
+Before delivering DCF model:
+
+**Required:**
+- Run `python recalc.py model.xlsx 30` until status is "success" (zero formula errors)
+- Two sheets: DCF (with sensitivity at bottom), WACC
+- Font colors: Blue=inputs, Black=formulas, Green=sheet links
+- Cell comments on ALL hardcoded inputs
+- Sensitivity tables fully populated with formulas
+- Professional borders around major sections
+
+**Validation:**
+- OpEx based on revenue (not gross profit)
+- Terminal value 50-70% of EV
+- Terminal growth < WACC
+- Tax rate 21-28%
+- File naming: `[Ticker]_DCF_Model_[Date].xlsx`
+
+## Data sources — MCP first, web fallback
+
+Many passages below say "use the S&P Kensho MCP / Daloopa MCP / FactSet MCP". Those are commercial financial-data MCPs from the original Cowork plugin context. In Hermes:
+
+- **If you have any structured financial-data MCP configured** (Hermes supports MCP — see `native-mcp` skill), prefer it for point-in-time comps, precedent transactions, and filings.
+- **Otherwise**, fall back to:
+  - `web_search` / `web_extract` against SEC EDGAR (`https://www.sec.gov/cgi-bin/browse-edgar`) for US filings
+  - Company IR pages for press releases, earnings decks
+  - `browser_navigate` for interactive data portals
+  - User-provided data (explicitly ask when the context doesn't have it)
+- **Never fabricate**. If a multiple, precedent, or filing number can't be sourced, flag the cell as `[UNSOURCED]` and surface it to the user.
+
+## Attribution
+
+This skill is adapted from Anthropic's Claude for Financial Services plugin suite (Apache-2.0). The Office-JS / Cowork live-Excel paths have been removed; this version targets headless openpyxl via the `excel-author` skill's conventions. Original: https://github.com/anthropics/financial-services
diff --git a/optional-skills/finance/dcf-model/TROUBLESHOOTING.md b/optional-skills/finance/dcf-model/TROUBLESHOOTING.md
new file mode 100644
index 0000000000..eb46365ca1
--- /dev/null
+++ b/optional-skills/finance/dcf-model/TROUBLESHOOTING.md
@@ -0,0 +1,40 @@
+# DCF Model Troubleshooting Guide
+
+**When to read this file:** If recalc.py shows errors OR valuation results seem unreasonable OR case selector not working properly.
+
+## Model Returns Error Values
+
+### #REF! Errors
+- Usually caused by formulas referencing wrong rows after headers were inserted
+- Solution: Rebuild with correct row references, or start over following layout planning
+- Prevention: Define all row positions BEFORE writing formulas
+
+### #DIV/0! Errors
+- Division by zero or empty cells
+- Solution: Add IF statements to handle zeros: `=IF([Divisor]=0,0,[Numerator]/[Divisor])`
+
+### #VALUE! Errors
+- Wrong data type in calculation (text instead of number)
+- Solution: Verify all inputs are formatted as numbers
+
+## Valuation Seems Unreasonable
+
+### Implied price far too high
+- Check terminal value isn't >80% of EV
+- Verify terminal growth < WACC
+- Review if growth assumptions are realistic
+- Consider if margins are too optimistic
+
+### Implied price far too low
+- Verify net debt vs net cash is correct
+- Check if WACC is too high
+- Review if projections are too conservative
+- Consider if terminal growth is too low
+
+## Case Selector Not Working
+
+### Consolidation column not updating when switching scenarios
+- Verify case selector cell contains 1, 2, or 3
+- Check INDEX/OFFSET formulas reference correct row range and selector cell
+- Ensure absolute references ($B$6) are used for selector
+- Test by manually changing the selector cell and verifying projection values update
diff --git a/optional-skills/finance/dcf-model/requirements.txt b/optional-skills/finance/dcf-model/requirements.txt
new file mode 100644
index 0000000000..0040dc4ada
--- /dev/null
+++ b/optional-skills/finance/dcf-model/requirements.txt
@@ -0,0 +1,7 @@
+# DCF Model Builder - Python Dependencies
+
+# Excel file handling
+openpyxl>=3.0.0
+
+# HTTP requests
+requests>=2.28.0
diff --git a/optional-skills/finance/dcf-model/scripts/validate_dcf.py b/optional-skills/finance/dcf-model/scripts/validate_dcf.py
new file mode 100755
index 0000000000..6c8172cf8c
--- /dev/null
+++ b/optional-skills/finance/dcf-model/scripts/validate_dcf.py
@@ -0,0 +1,292 @@
+#!/usr/bin/env python3
+"""
+DCF Model Validation Script
+Validates Excel DCF models for formula errors and common DCF mistakes
+"""
+
+import sys
+import json
+from pathlib import Path
+from typing import Optional
+
+
+class DCFModelValidator:
+    """Validates DCF models for errors and quality issues"""
+
+    def __init__(self, excel_path: str):
+        try:
+            import openpyxl
+        except ImportError:
+            raise ImportError("openpyxl not installed. Run: pip install openpyxl")
+
+        self.excel_path = excel_path
+        self.openpyxl = openpyxl
+
+        if not Path(excel_path).exists():
+            raise FileNotFoundError(f"File not found: {excel_path}")
+
+        self.workbook_formulas = openpyxl.load_workbook(excel_path, data_only=False)
+        self.workbook_values = openpyxl.load_workbook(excel_path, data_only=True)
+        self.errors = []
+        self.warnings = []
+        self.info = []
+        
+    def validate_all(self) -> dict:
+        """
+        Run all validation checks
+
+        Returns:
+            Dict with validation results
+        """
+        from datetime import datetime
+
+        self.check_sheet_structure()
+        self.check_formula_errors()
+        self.check_dcf_logic()
+
+        results = {
+            'file': self.excel_path,
+            'validation_date': datetime.now().isoformat(),
+            'status': 'PASS' if len(self.errors) == 0 else 'FAIL',
+            'error_count': len(self.errors),
+            'warning_count': len(self.warnings),
+            'errors': self.errors,
+            'warnings': self.warnings,
+            'info': self.info
+        }
+
+        return results
+    
+    def check_sheet_structure(self):
+        """Verify required sheets exist"""
+        required_sheets = ['DCF', 'WACC', 'Sensitivity']
+        sheet_names = self.workbook_values.sheetnames
+
+        for sheet in required_sheets:
+            if sheet not in sheet_names:
+                self.warnings.append(f"Recommended sheet missing: {sheet}")
+            else:
+                self.info.append(f"Found sheet: {sheet}")
+
+    def check_formula_errors(self):
+        """Check for Excel formula errors in all sheets"""
+        excel_errors = ['#VALUE!', '#DIV/0!', '#REF!', '#NAME?', '#NULL!', '#NUM!', '#N/A']
+        error_details = {err: [] for err in excel_errors}
+        total_errors = 0
+        total_formulas = 0
+
+        for sheet_name in self.workbook_values.sheetnames:
+            ws_values = self.workbook_values[sheet_name]
+            ws_formulas = self.workbook_formulas[sheet_name]
+
+            for row in ws_values.iter_rows():
+                for cell in row:
+                    formula_cell = ws_formulas[cell.coordinate]
+
+                    # Count formulas
+                    if formula_cell.value and isinstance(formula_cell.value, str) and formula_cell.value.startswith('='):
+                        total_formulas += 1
+
+                    # Check for errors
+                    if cell.value is not None and isinstance(cell.value, str):
+                        for err in excel_errors:
+                            if err in cell.value:
+                                location = f"{sheet_name}!{cell.coordinate}"
+                                error_details[err].append(location)
+                                total_errors += 1
+                                self.errors.append(f"{err} at {location}")
+                                break
+
+        # Add summary info
+        self.info.append(f"Total formulas: {total_formulas}")
+        if total_errors == 0:
+            self.info.append("✓ No formula errors found")
+        else:
+            self.errors.append(f"Total formula errors: {total_errors}")
+
+        return error_details, total_errors
+    
+    def check_dcf_logic(self):
+        """Validate DCF-specific logic and calculations"""
+        self._check_terminal_growth_vs_wacc()
+        self._check_wacc_range()
+        self._check_terminal_value_proportion()
+
+    def _check_terminal_growth_vs_wacc(self):
+        """Critical check: Terminal growth must be less than WACC"""
+        try:
+            dcf_sheet = self.workbook_values['DCF']
+
+            terminal_growth = None
+            wacc = None
+
+            # Search for terminal growth and WACC values
+            for row in dcf_sheet.iter_rows(max_row=100, max_col=20):
+                for cell in row:
+                    if cell.value and isinstance(cell.value, str):
+                        cell_str = cell.value.lower()
+                        if 'terminal' in cell_str and 'growth' in cell_str:
+                            # Look for value in adjacent cells
+                            for offset in range(1, 5):
+                                adjacent = dcf_sheet.cell(cell.row, cell.column + offset).value
+                                if isinstance(adjacent, (int, float)) and 0 < adjacent < 1:
+                                    terminal_growth = adjacent
+                                    break
+                        if 'wacc' in cell_str and wacc is None:
+                            for offset in range(1, 5):
+                                adjacent = dcf_sheet.cell(cell.row, cell.column + offset).value
+                                if isinstance(adjacent, (int, float)) and 0 < adjacent < 1:
+                                    wacc = adjacent
+                                    break
+
+            if terminal_growth is not None and wacc is not None:
+                if terminal_growth >= wacc:
+                    self.errors.append(
+                        f"CRITICAL: Terminal growth ({terminal_growth:.2%}) >= WACC ({wacc:.2%}). "
+                        "This creates infinite value and is mathematically invalid."
+                    )
+                else:
+                    self.info.append(
+                        f"✓ Terminal growth ({terminal_growth:.2%}) < WACC ({wacc:.2%})"
+                    )
+            else:
+                self.warnings.append("Could not locate terminal growth and WACC values")
+
+        except KeyError:
+            self.warnings.append("DCF sheet not found")
+        except Exception as e:
+            self.warnings.append(f"Could not validate terminal growth vs WACC: {str(e)}")
+
+    def _check_wacc_range(self):
+        """Check if WACC is in reasonable range"""
+        try:
+            wacc_sheet = self.workbook_values.get('WACC') or self.workbook_values['DCF']
+            wacc = None
+
+            for row in wacc_sheet.iter_rows(max_row=100, max_col=20):
+                for cell in row:
+                    if cell.value and isinstance(cell.value, str):
+                        if 'wacc' in cell.value.lower():
+                            for offset in range(1, 5):
+                                adjacent = wacc_sheet.cell(cell.row, cell.column + offset).value
+                                if isinstance(adjacent, (int, float)) and 0 < adjacent < 1:
+                                    wacc = adjacent
+                                    break
+
+            if wacc is not None:
+                if wacc < 0.05 or wacc > 0.20:
+                    self.warnings.append(
+                        f"WACC ({wacc:.2%}) is outside typical range (5%-20%). Verify calculation."
+                    )
+                else:
+                    self.info.append(f"✓ WACC ({wacc:.2%}) in reasonable range")
+            else:
+                self.warnings.append("Could not locate WACC value")
+
+        except Exception as e:
+            self.warnings.append(f"Could not validate WACC range: {str(e)}")
+
+    def _check_terminal_value_proportion(self):
+        """Check if terminal value is reasonable proportion of enterprise value"""
+        try:
+            dcf_sheet = self.workbook_values['DCF']
+
+            terminal_value = None
+            enterprise_value = None
+
+            for row in dcf_sheet.iter_rows(max_row=200, max_col=20):
+                for cell in row:
+                    if cell.value and isinstance(cell.value, str):
+                        cell_str = cell.value.lower()
+                        if 'terminal' in cell_str and 'value' in cell_str and 'pv' in cell_str:
+                            for offset in range(1, 5):
+                                adjacent = dcf_sheet.cell(cell.row, cell.column + offset).value
+                                if isinstance(adjacent, (int, float)) and adjacent > 0:
+                                    terminal_value = adjacent
+                                    break
+                        if 'enterprise' in cell_str and 'value' in cell_str:
+                            for offset in range(1, 5):
+                                adjacent = dcf_sheet.cell(cell.row, cell.column + offset).value
+                                if isinstance(adjacent, (int, float)) and adjacent > 0:
+                                    enterprise_value = adjacent
+                                    break
+
+            if terminal_value is not None and enterprise_value is not None and enterprise_value > 0:
+                proportion = terminal_value / enterprise_value
+                if proportion > 0.80:
+                    self.warnings.append(
+                        f"Terminal value is {proportion:.1%} of EV (typically should be 50-70%). "
+                        "Model may be over-reliant on terminal assumptions."
+                    )
+                elif proportion < 0.40:
+                    self.warnings.append(
+                        f"Terminal value is {proportion:.1%} of EV (typically should be 50-70%). "
+                        "Check if terminal assumptions are too conservative."
+                    )
+                else:
+                    self.info.append(f"✓ Terminal value is {proportion:.1%} of EV")
+            else:
+                self.warnings.append("Could not locate terminal value and enterprise value")
+
+        except Exception as e:
+            self.warnings.append(f"Could not validate terminal value proportion: {str(e)}")
+    
+
+
+def validate_dcf_model(excel_path: str) -> dict:
+    """
+    Validate a DCF model Excel file
+
+    Args:
+        excel_path: Path to Excel DCF model
+
+    Returns:
+        Dict with validation results
+    """
+    validator = DCFModelValidator(excel_path)
+    return validator.validate_all()
+
+
+def main():
+    """Command-line interface"""
+    if len(sys.argv) < 2:
+        print("Usage: python validate_dcf.py <excel_file> [output.json]")
+        print("\nValidates DCF model for:")
+        print("  - Formula errors (#REF!, #DIV/0!, etc.)")
+        print("  - Terminal growth < WACC (critical)")
+        print("  - WACC in reasonable range (5-20%)")
+        print("  - Terminal value proportion of EV (40-80%)")
+        print("\nReturns JSON with errors, warnings, and info")
+        print("\nExample: python validate_dcf.py model.xlsx")
+        print("Example: python validate_dcf.py model.xlsx results.json")
+        sys.exit(1)
+
+    excel_file = sys.argv[1]
+    output_file = sys.argv[2] if len(sys.argv) > 2 else None
+
+    try:
+        results = validate_dcf_model(excel_file)
+
+        # Print results
+        print(json.dumps(results, indent=2))
+
+        # Save to file if requested
+        if output_file:
+            with open(output_file, 'w') as f:
+                json.dump(results, f, indent=2)
+
+        # Exit with error code if validation failed
+        sys.exit(0 if results['status'] == 'PASS' else 1)
+
+    except Exception as e:
+        error_result = {
+            'file': excel_file,
+            'status': 'ERROR',
+            'error': str(e)
+        }
+        print(json.dumps(error_result, indent=2))
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/optional-skills/finance/excel-author/SKILL.md b/optional-skills/finance/excel-author/SKILL.md
new file mode 100644
index 0000000000..1a46b40939
--- /dev/null
+++ b/optional-skills/finance/excel-author/SKILL.md
@@ -0,0 +1,243 @@
+---
+name: excel-author
+description: Build auditable Excel workbooks headless with openpyxl — blue/black/green cell conventions, formulas over hardcodes, named ranges, balance checks, sensitivity tables. Use for financial models, audit outputs, reconciliations.
+version: 1.0.0
+author: Anthropic (adapted by Nous Research)
+license: Apache-2.0
+metadata:
+  hermes:
+    tags: [excel, openpyxl, finance, spreadsheet, modeling]
+    related_skills: [pptx-author, dcf-model, comps-analysis, lbo-model, 3-statement-model]
+---
+
+# excel-author
+
+Produce an .xlsx file on disk using `openpyxl`. Follow the banker-grade conventions below so the model is auditable, flexible, and reviewable by someone other than the person who built it.
+
+Adapted from Anthropic's `xlsx-author` and `audit-xls` skills in the [anthropics/financial-services](https://github.com/anthropics/financial-services) repo. The MCP / Office-JS / Cowork-specific branches of the originals are dropped — this skill assumes headless Python.
+
+## Output contract
+
+- Write to `./out/<name>.xlsx`. Create `./out/` if it does not exist.
+- Return the relative path in your final message so downstream tools can pick it up.
+- One logical model per file. Do not append to an existing workbook unless explicitly asked.
+
+## Setup
+
+```bash
+pip install "openpyxl>=3.0"
+```
+
+## Core conventions (non-negotiable)
+
+### Blue / black / green cell color
+- **Blue** (`Font(color="0000FF")`) — hardcoded input a human entered. Revenue drivers, WACC inputs, terminal growth, market data.
+- **Black** (default) — formula. Every derived cell is a live Excel formula.
+- **Green** (`Font(color="006100")`) — link to another sheet or external file.
+
+A reviewer can then scan the sheet and immediately see what's an assumption vs. what's computed.
+
+### Formulas over hardcodes
+Every calculation cell MUST be a formula string, never a number computed in Python and pasted as a value.
+
+```python
+# WRONG — silent bug waiting to happen
+ws["D20"] = revenue_prior_year * (1 + growth)
+
+# CORRECT — flexes when the user changes the assumption
+ws["D20"] = "=D19*(1+$B$8)"
+```
+
+The only hardcoded numbers permitted:
+1. Raw historical inputs (actual revenues, reported EBITDA, etc.)
+2. Assumption drivers the user is meant to flex (growth rates, WACC inputs, terminal g)
+3. Current market data (share price, debt balance) — with a cell comment documenting source + date
+
+If you catch yourself computing a value in Python and writing the result, stop.
+
+### Named ranges for cross-sheet references
+Use named ranges for any figure referenced from another sheet, a deck, or a memo.
+
+```python
+from openpyxl.workbook.defined_name import DefinedName
+wb.defined_names["WACC"] = DefinedName("WACC", attr_text="Inputs!$C$8")
+# then elsewhere:
+calc["D30"] = "=D29/WACC"
+```
+
+### Balance checks tab
+Include a `Checks` tab that ties everything and surfaces TRUE/FALSE:
+- Balance sheet balances (assets = liabilities + equity)
+- Cash flow ties to period-over-period cash change on the BS
+- Sum-of-parts ties to consolidated totals
+- No rogue hardcodes inside calc ranges
+
+Example:
+```python
+checks = wb.create_sheet("Checks")
+checks["A2"] = "BS balances"
+checks["B2"] = "=IS!D20-IS!D21-IS!D22"
+checks["C2"] = "=ABS(B2)<0.01"  # TRUE/FALSE
+```
+
+### Cell comments on every hardcoded input
+Add the comment AS you create the cell, not later.
+
+```python
+from openpyxl.comments import Comment
+ws["C2"] = 1_250_000_000
+ws["C2"].font = Font(color="0000FF")
+ws["C2"].comment = Comment("Source: 10-K FY2024, p.47, revenue line", "analyst")
+```
+
+Format: `Source: [System/Document], [Date], [Reference], [URL if applicable]`.
+
+Never defer sourcing. Never write `TODO: add source`.
+
+## Skeleton: typical financial model
+
+```python
+from openpyxl import Workbook
+from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
+from openpyxl.comments import Comment
+from openpyxl.utils import get_column_letter
+from pathlib import Path
+
+BLUE = Font(color="0000FF")
+BLACK = Font(color="000000")
+GREEN = Font(color="006100")
+BOLD = Font(bold=True)
+HEADER_FILL = PatternFill("solid", fgColor="1F4E79")
+HEADER_FONT = Font(color="FFFFFF", bold=True)
+
+wb = Workbook()
+
+# --- Inputs tab ---
+inp = wb.active
+inp.title = "Inputs"
+inp["A1"] = "MARKET DATA & KEY INPUTS"
+inp["A1"].font = HEADER_FONT
+inp["A1"].fill = HEADER_FILL
+inp.merge_cells("A1:C1")
+
+inp["B3"] = "Revenue FY2024"
+inp["C3"] = 1_250_000_000
+inp["C3"].font = BLUE
+inp["C3"].comment = Comment("Source: 10-K FY2024 p.47", "model")
+
+inp["B4"] = "Growth Rate"
+inp["C4"] = 0.12
+inp["C4"].font = BLUE
+
+# --- Calc tab ---
+calc = wb.create_sheet("DCF")
+calc["B2"] = "Projected Revenue"
+calc["C2"] = "=Inputs!C3*(1+Inputs!C4)"   # formula, black
+
+# --- Checks tab ---
+chk = wb.create_sheet("Checks")
+chk["A2"] = "BS balances"
+chk["B2"] = "=ABS(BS!D20-BS!D21-BS!D22)<0.01"
+
+Path("./out").mkdir(exist_ok=True)
+wb.save("./out/model.xlsx")
+```
+
+## Section headers with merged cells
+
+openpyxl quirk: when you merge, set the value on the top-left cell and style the full range separately.
+
+```python
+ws["A7"] = "CASH FLOW PROJECTION"
+ws["A7"].font = HEADER_FONT
+ws.merge_cells("A7:H7")
+for col in range(1, 9):  # A..H
+    ws.cell(row=7, column=col).fill = HEADER_FILL
+```
+
+## Sensitivity tables
+
+Build with loops, not hardcoded formulas per cell. Rules:
+
+- **Odd number of rows/cols** (5×5 or 7×7) — guarantees a true center cell.
+- **Center cell = base case.** The middle row/col header must equal the model's actual WACC and terminal g so the center output equals the base-case implied share price. That's the sanity check.
+- **Highlight the center cell** with medium-blue fill (`"BDD7EE"`) and bold.
+- Populate every cell with a full recalculation formula — never an approximation.
+
+```python
+# 5x5 WACC (rows) x terminal growth (cols) sensitivity
+wacc_axis = [0.08, 0.085, 0.09, 0.095, 0.10]        # center row = base 9.0%
+term_axis = [0.02, 0.025, 0.03, 0.035, 0.04]        # center col = base 3.0%
+
+start_row = 40
+ws.cell(row=start_row, column=1).value = "Implied Share Price ($)"
+ws.cell(row=start_row, column=1).font = BOLD
+
+for j, g in enumerate(term_axis):
+    ws.cell(row=start_row+1, column=2+j).value = g
+    ws.cell(row=start_row+1, column=2+j).font = BLUE
+
+for i, w in enumerate(wacc_axis):
+    r = start_row + 2 + i
+    ws.cell(row=r, column=1).value = w
+    ws.cell(row=r, column=1).font = BLUE
+    for j, g in enumerate(term_axis):
+        c = 2 + j
+        # Full DCF recalc formula (simplified for illustration).
+        # In a real model this references the full projection block.
+        ws.cell(row=r, column=c).value = (
+            f"=SUMPRODUCT(FCF_range,1/(1+{w})^year_offset) + "
+            f"FCF_terminal*(1+{g})/({w}-{g})/(1+{w})^terminal_year"
+        )
+
+# Highlight center cell (base case)
+center = ws.cell(row=start_row+2+len(wacc_axis)//2,
+                 column=2+len(term_axis)//2)
+center.fill = PatternFill("solid", fgColor="BDD7EE")
+center.font = BOLD
+```
+
+## Recalculating before delivery
+
+openpyxl writes formula strings but does not compute them. Excel recalculates on open, but downstream consumers (auto-check scripts, CI) need computed values.
+
+Run LibreOffice or a dedicated recalc step before delivery:
+
+```bash
+# LibreOffice headless recalc
+libreoffice --headless --calc --convert-to xlsx ./out/model.xlsx --outdir ./out/
+```
+
+Or use a Python recalc helper (see `scripts/recalc.py` in this skill).
+
+## Model layout planning
+
+Before writing any formula:
+1. Define ALL section row positions
+2. Write ALL headers and labels
+3. Write ALL section dividers and blank rows
+4. THEN write formulas using the locked row positions
+
+This prevents the cascading-formula-breakage pattern where inserting a header row after formulas are written shifts every downstream reference.
+
+## Verify step-by-step with the user
+
+For large models (DCFs, 3-statement, LBO), stop and show the user intermediate artifacts before continuing. Catching a wrong margin assumption before you've built downstream sensitivity tables saves an hour.
+
+Checkpoint pattern:
+- After Inputs block → show raw inputs, confirm before projecting
+- After Revenue projections → confirm top line + growth
+- After FCF build → confirm the full schedule
+- After WACC → confirm inputs
+- After valuation → confirm the equity bridge
+- THEN build sensitivity tables
+
+## When NOT to use this skill
+
+- Users in a live Excel session with an Office MCP available — drive their live workbook instead.
+- Pure tabular data export with no formulas — `csv` or `pandas.to_excel` is simpler.
+- Dashboards / charts with heavy interactivity — use a real BI tool.
+
+## Attribution
+
+Conventions (blue/black/green, formulas-over-hardcodes, named ranges, sensitivity rules) adapted from Anthropic's Claude for Financial Services plugin suite, Apache-2.0 licensed. Original: https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/xlsx-author
diff --git a/optional-skills/finance/excel-author/scripts/recalc.py b/optional-skills/finance/excel-author/scripts/recalc.py
new file mode 100644
index 0000000000..a329dbe724
--- /dev/null
+++ b/optional-skills/finance/excel-author/scripts/recalc.py
@@ -0,0 +1,88 @@
+#!/usr/bin/env python3
+"""Recalculate an .xlsx file's formulas using LibreOffice headless.
+
+Usage: python recalc.py <path.xlsx> [timeout_seconds]
+
+openpyxl writes formula strings but does not compute them. Downstream scripts
+that open the file with data_only=True get None for every formula cell until
+something has actually calculated the workbook. Excel does this on open;
+headless pipelines need LibreOffice (or similar) to do it explicitly.
+
+Exits 0 on success (workbook recomputed and resaved in place), non-zero on
+failure. Writes status JSON to stdout either way.
+"""
+
+import json
+import shutil
+import subprocess
+import sys
+import tempfile
+from pathlib import Path
+
+
+def find_libreoffice() -> str | None:
+    for cmd in ("libreoffice", "soffice"):
+        path = shutil.which(cmd)
+        if path:
+            return path
+    return None
+
+
+def recalc(xlsx_path: str, timeout: int = 60) -> dict:
+    src = Path(xlsx_path).resolve()
+    if not src.exists():
+        return {"status": "error", "error": f"File not found: {src}"}
+
+    lo = find_libreoffice()
+    if lo is None:
+        return {
+            "status": "error",
+            "error": "libreoffice not found on PATH — install it or recalc in a real Excel session",
+        }
+
+    with tempfile.TemporaryDirectory() as td:
+        try:
+            subprocess.run(
+                [
+                    lo,
+                    "--headless",
+                    "--calc",
+                    "--convert-to",
+                    "xlsx",
+                    str(src),
+                    "--outdir",
+                    td,
+                ],
+                check=True,
+                capture_output=True,
+                timeout=timeout,
+            )
+        except subprocess.TimeoutExpired:
+            return {"status": "error", "error": f"libreoffice timed out after {timeout}s"}
+        except subprocess.CalledProcessError as e:
+            return {
+                "status": "error",
+                "error": f"libreoffice exited {e.returncode}: {e.stderr.decode(errors='replace')[:500]}",
+            }
+
+        produced = Path(td) / src.name
+        if not produced.exists():
+            return {"status": "error", "error": "libreoffice did not produce output file"}
+
+        shutil.copy(produced, src)
+
+    return {"status": "success", "file": str(src)}
+
+
+def main():
+    if len(sys.argv) < 2:
+        print("Usage: python recalc.py <path.xlsx> [timeout_seconds]", file=sys.stderr)
+        sys.exit(2)
+    timeout = int(sys.argv[2]) if len(sys.argv) > 2 else 60
+    result = recalc(sys.argv[1], timeout=timeout)
+    print(json.dumps(result, indent=2))
+    sys.exit(0 if result["status"] == "success" else 1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/optional-skills/finance/lbo-model/SKILL.md b/optional-skills/finance/lbo-model/SKILL.md
new file mode 100644
index 0000000000..03fd0cbe56
--- /dev/null
+++ b/optional-skills/finance/lbo-model/SKILL.md
@@ -0,0 +1,290 @@
+---
+name: lbo-model
+description: Build leveraged buyout models in Excel — sources & uses, debt schedule, cash sweep, exit multiple, IRR/MOIC sensitivity. Pairs with excel-author. Use for PE screening, sponsor-case valuation, or illustrative LBO in a pitch.
+version: 1.0.0
+author: Anthropic (adapted by Nous Research)
+license: Apache-2.0
+metadata:
+  hermes:
+    tags: [finance, valuation, lbo, private-equity, excel, openpyxl, modeling]
+    related_skills: [excel-author, pptx-author, dcf-model, 3-statement-model]
+---
+
+## Environment
+
+This skill assumes **headless openpyxl** — you are producing an .xlsx file on disk.
+Follow the `excel-author` skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables.
+Recalculate before delivery: `python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx`.
+
+---
+
+## TEMPLATE REQUIREMENT
+
+**This skill uses templates for LBO models. Always check for an attached template file first.**
+
+Before starting any LBO model:
+1. **If a template file is attached/provided**: Use that template's structure exactly - copy it and populate with the user's data
+2. **If no template is attached**: Ask the user: *"Do you have a specific LBO template you'd like me to use? If not, I can use the standard template which includes Sources & Uses, Operating Model, Debt Schedule, and Returns Analysis."*
+3. **If using the standard template**: Copy `examples/LBO_Model.xlsx` as your starting point and populate it with the user's assumptions
+
+**IMPORTANT**: When a file like `LBO_Model.xlsx` is attached, you MUST use it as your template - do not build from scratch. Even if the template seems complex or has more features than needed, copy it and adapt it to the user's requirements. Never decide to "build from scratch" when a template is provided.
+
+---
+
+## CRITICAL INSTRUCTIONS — READ FIRST
+
+Use Python/openpyxl. Write formula strings (`ws["D20"] = "=B5*B6"`), then run the `excel-author` skill's `recalc.py` helper before delivery.
+
+### Core Principles
+* **Every calculation must be an Excel formula** - NEVER compute values in Python and hardcode results into cells. When using openpyxl, write `cell.value = "=B5*B6"` (formula string), NOT `cell.value = 1250` (computed result). The model must be dynamic and update when inputs change.
+* **Use the template structure** - Follow the organization in `examples/LBO_Model.xlsx` or the user's provided template. Do not invent your own layout.
+* **Use proper cell references** - All formulas should reference the appropriate cells. Never type numbers that should come from other cells.
+* **Maintain sign convention consistency** - Follow whatever sign convention the template uses (some use negative for outflows, some use positive). Be consistent throughout.
+* **Work section by section, verify with user at each step** - Complete one section fully, show the user what was built, run the section's verification checks, and get confirmation BEFORE moving to the next section. Do NOT build the entire model end-to-end and then present it — later sections depend on earlier ones, so catching a mistake in Sources & Uses after the returns are already built means rework everywhere.
+
+### Formula Color Conventions
+* **Blue (0000FF)**: Hardcoded inputs - typed numbers that don't reference other cells
+* **Black (000000)**: Formulas with calculations - any formula using operators or functions (`=B4*B5`, `=SUM()`, `=-MAX(0,B4)`)
+* **Purple (800080)**: Links to cells on the **same tab** - direct references with no calculation (`=B9`, `=B45`)
+* **Green (008000)**: Links to cells on **different tabs** - cross-sheet references (`=Assumptions!B5`, `='Operating Model'!C10`)
+
+### Fill Color Palette — Professional Blues & Greys (Default unless user/template specifies otherwise)
+* **Keep it minimal** — only use blues and greys for cell fills. Do NOT introduce greens, yellows, reds, or multiple accents. A professional LBO model uses restraint.
+* **Default fill palette:**
+  * **Section headers** (Sources & Uses, Operating Model, etc.): Dark blue `#1F4E79` with white bold text
+  * **Column headers** (Year 1, Year 2, etc.): Light blue `#D9E1F2` with black bold text
+  * **Input cells**: Light grey `#F2F2F2` (or just white) — the blue *font* is the signal, fill is secondary
+  * **Formula/calculated cells**: White, no fill
+  * **Key outputs** (IRR, MOIC, Exit Equity): Medium blue `#BDD7EE` with black bold text
+* **That's the whole palette.** 3 blues + 1 grey + white. If the template uses its own colors, follow the template instead.
+* Note: The blue/black/purple/green **font** colors above are for distinguishing inputs vs formulas vs links. Those are separate from the **fill** palette here — both work together.
+
+### Number Formatting Standards
+* **Currency**: `$#,##0;($#,##0);"-"` or `$#,##0.0` depending on template
+* **Percentages**: `0.0%` (one decimal)
+* **Multiples**: `0.0"x"` (one decimal)
+* **MOIC/Detailed Ratios**: `0.00"x"` (two decimals for precision)
+* **All numeric cells**: Right-aligned
+
+---
+
+### Clarify Requirements First
+
+Before filling any formulas:
+
+* **Examine the template structure** - Identify all sections, understand the timeline (which columns are which periods), note any existing formulas
+* **Ask the user if anything is unclear** - If the template structure, calculation methods, or requirements are ambiguous, ask before proceeding
+* **Confirm key assumptions** - Any key inputs, calculation preferences, or specific requirements
+* **ONLY AFTER understanding the template**, proceed to fill in formulas
+
+---
+
+## TEMPLATE ANALYSIS PHASE - DO THIS FIRST
+
+Before filling any formulas, examine the template thoroughly:
+
+1. **Map the structure** - Identify where each section lives and how they relate to each other. Note which sections feed into others.
+
+2. **Understand the timeline** - Which columns represent which periods? Is there a "Closing" or "Pro Forma" column? Where does the projection period start?
+
+3. **Identify input vs formula cells** - Templates often use color coding, borders, or shading to indicate which cells need inputs vs formulas. Respect these conventions.
+
+4. **Read existing labels carefully** - The row labels tell you exactly what calculation is expected. Don't assume - read what the template is asking for.
+
+5. **Check for existing formulas** - Some templates come partially filled. Don't overwrite working formulas unless specifically asked.
+
+6. **Note template-specific conventions** - Sign conventions, subtotal structures, how sections are organized, whether there are separate tabs for different components, etc.
+
+---
+
+## FILLING FORMULAS - GENERAL APPROACH
+
+For each cell that needs a formula, follow this hierarchy:
+
+### Step 1: Check the Template
+* Does the cell already have a formula? If yes, verify it's correct and move on.
+* Is there a comment or note indicating the expected calculation?
+* Does the row/column label make the calculation obvious?
+* Do neighboring cells show a pattern you should follow?
+
+### Step 2: Check the User's Instructions
+* Did the user specify a particular calculation method?
+* Are there stated assumptions that affect this formula?
+* Any special requirements mentioned?
+
+### Step 3: Apply Standard Practice
+* If neither template nor user specifies, use standard LBO modeling conventions
+* Document any assumptions you make
+* If genuinely uncertain, ask the user
+
+---
+
+## COMMON PROBLEM AREAS
+
+The following calculation patterns frequently cause issues across LBO models. Pay special attention when you encounter these:
+
+### Balancing Sections
+* When two sections must equal (e.g., Sources = Uses), one item is typically the "plug" (balancing figure)
+* Identify which item is the plug and calculate it as the difference
+
+### Tax Calculations
+* Tax formulas should only reference the relevant income line and tax rate
+* Should NOT reference unrelated sections (e.g., debt schedules)
+* Consider whether losses create tax shields or are simply ignored
+
+### Interest and Circular References
+* Interest calculations can create circularity if they reference balances affected by cash flows
+* Use **Beginning Balance** (not average or ending) to break circular references
+* Pattern: Interest → Cash Flow → Paydown → Ending Balance (if interest uses ending balance, this circles back)
+
+### Debt Paydown / Cash Sweeps
+* When multiple debt tranches exist, there's usually a priority order
+* Cash sweep should respect the priority waterfall
+* Balances cannot go negative - use MAX or MIN functions appropriately
+
+### Returns Calculations (IRR/MOIC)
+* Cash flows must have correct signs: Investment = negative, Proceeds = positive
+* If using XIRR, need corresponding dates
+* If using IRR, cash flows should be in consecutive periods
+* MOIC = Total Proceeds / Total Investment
+
+### Sensitivity Tables
+* **Use ODD dimensions** (5×5 or 7×7) — never 4×4 or 6×6. Odd dimensions guarantee a true center cell.
+* **Center cell = base case.** Build the row and column axis values symmetrically around the model's actual assumptions (e.g., if base entry multiple = 10.0x, axis = `[8.0x, 9.0x, 10.0x, 11.0x, 12.0x]`). The center cell's IRR/MOIC MUST then equal the model's actual IRR/MOIC output — this is the proof the table is wired correctly.
+* **Highlight the center cell** — medium-blue fill (`#BDD7EE`) + bold font so the base case is visually anchored.
+* Excel's DATA TABLE function may not work with openpyxl — instead write explicit formulas that reference row/column headers
+* Each cell should show a DIFFERENT value — if all same, formulas aren't varying correctly
+* Use mixed references (e.g., `$A5` for row input, `B$4` for column input)
+
+---
+
+## VERIFICATION CHECKLIST - RUN AFTER COMPLETION
+
+### Run Formula Validation
+```bash
+python /path/to/excel-author/scripts/recalc.py model.xlsx
+```
+Must return success with zero errors.
+
+### Section Balancing
+- [ ] Any sections that must balance (Sources/Uses, Assets/Liabilities) balance exactly
+- [ ] Plug items are calculated correctly as the balancing figure
+- [ ] Amounts that should match across sections are consistent
+
+### Income/Operating Projections
+- [ ] Revenue/top-line builds correctly from drivers or growth rates
+- [ ] All cost and expense items calculated appropriately
+- [ ] Subtotals and totals sum correctly
+- [ ] Margins and ratios are reasonable
+- [ ] Links to assumptions are correct
+
+### Balance Sheet (if applicable)
+- [ ] Assets = Liabilities + Equity (must balance)
+- [ ] All items link to appropriate schedules or roll-forwards
+- [ ] Beginning balances = prior period ending balances
+- [ ] Check row included and shows zero
+
+### Cash Flow (if applicable)
+- [ ] Starts with correct income figure
+- [ ] Non-cash items added/subtracted appropriately
+- [ ] Working capital changes have correct signs
+- [ ] Ending Cash = Beginning Cash + Net Cash Flow
+- [ ] Cash balances are consistent across statements
+
+### Supporting Schedules
+- [ ] Roll-forward schedules balance (Beginning + Changes = Ending)
+- [ ] Schedules link correctly to main statements
+- [ ] Calculated items use appropriate drivers
+- [ ] All periods are calculated consistently
+
+### Debt/Financing Schedules (if applicable)
+- [ ] Beginning balances tie to sources or prior period
+- [ ] Interest calculated on appropriate balance (typically beginning)
+- [ ] Paydowns respect cash availability and priority
+- [ ] Ending balances cannot be negative
+- [ ] Totals sum tranches correctly
+
+### Returns/Output Analysis
+- [ ] Exit/terminal values calculated correctly
+- [ ] All relevant adjustments included
+- [ ] Cash flow signs are correct (negative for investment, positive for proceeds)
+- [ ] IRR/MOIC formulas reference complete ranges
+- [ ] Results are reasonable for the scenario
+
+### Sensitivity Tables (if applicable)
+- [ ] Grid dimensions are ODD (5×5 or 7×7) — there is a true center cell
+- [ ] Row and column axis values are symmetric around the base case (`[base-2Δ, base-Δ, base, base+Δ, base+2Δ]`)
+- [ ] Center cell output equals the model's actual IRR/MOIC — confirms the table is wired correctly
+- [ ] Center cell is highlighted (medium-blue fill `#BDD7EE`, bold font)
+- [ ] Row and column headers contain appropriate input values
+- [ ] Each data cell contains a formula (not hardcoded)
+- [ ] Each data cell shows a DIFFERENT value
+- [ ] Values move in expected directions (higher exit multiple → higher IRR, etc.)
+
+### Formatting
+- [ ] Hardcoded inputs are blue (0000FF)
+- [ ] Calculated formulas are black (000000)
+- [ ] Same-tab links are purple (800080)
+- [ ] Cross-tab links are green (008000)
+- [ ] All numbers are right-aligned
+- [ ] Appropriate number formats applied throughout
+- [ ] No cells show error values (#REF!, #DIV/0!, #VALUE!, #NAME?)
+
+### Logical Sanity Checks
+- [ ] Numbers are reasonable order of magnitude
+- [ ] Trends make sense (growth, decline, stabilization as expected)
+- [ ] No obviously wrong values (negative where should be positive, impossible percentages, etc.)
+- [ ] Key outputs are within reasonable ranges for the type of analysis
+
+---
+
+## COMMON ERRORS TO AVOID
+
+| Error | What Goes Wrong | How to Fix |
+|-------|-----------------|------------|
+| Hardcoding calculated values | Model doesn't update when inputs change | Always use formulas that reference source cells |
+| Wrong cell references after copying | Formulas point to wrong cells | Verify all links, use appropriate $ anchoring |
+| Circular reference errors | Model can't calculate | Use beginning balances for interest-type calcs, break the circle |
+| Sections don't balance | Totals that should match don't | Ensure one item is the plug (calculated as difference) |
+| Negative balances where impossible | Paying/using more than available | Use MAX(0, ...) or MIN functions appropriately |
+| IRR/return errors | Wrong signs or incomplete ranges | Check cash flow signs and ensure formula covers all periods |
+| Sensitivity table shows same value | Formula not varying with inputs | Check cell references - need mixed references ($A5, B$4) |
+| Roll-forwards don't tie | Beginning ≠ prior ending | Verify links between periods |
+| Inconsistent sign conventions | Additions become subtractions or vice versa | Follow template's convention consistently throughout |
+
+---
+
+## WORKING WITH THE USER — SECTION-BY-SECTION CHECKPOINTS
+
+* **If the template structure is unclear**, ask before proceeding
+* **If the user's requirements conflict with the template**, confirm their preference
+* **After completing each major section**, STOP and verify with the user before continuing:
+  - **After Sources & Uses** → show the balanced table, confirm the plug is correct, get sign-off before building the operating model
+  - **After Operating Model / Projections** → show the projected P&L, confirm growth rates and margins look right, get sign-off before the debt schedule
+  - **After Debt Schedule** → show beginning/ending balances and interest, confirm the waterfall logic, get sign-off before returns
+  - **After Returns (IRR/MOIC)** → show the cash flow series and outputs, confirm signs and ranges, get sign-off before sensitivity tables
+  - **After Sensitivity Tables** → show that each cell varies, confirm the base case lands where expected
+* **If errors are found during verification**, fix them before moving to the next section
+* **Show your work** - explain key formulas or assumptions when helpful
+* **Never present a completed model without having checked in at each section** — it's faster to catch a wrong cell reference at the source than to trace it backwards from a broken IRR
+
+---
+
+**This skill produces investment banking-quality LBO models by filling templates with correct formulas, proper formatting, and validated calculations. The skill adapts to any template structure while ensuring financial accuracy and professional presentation standards.**
+
+
+## Data sources — MCP first, web fallback
+
+Many passages below say "use the S&P Kensho MCP / Daloopa MCP / FactSet MCP". Those are commercial financial-data MCPs from the original Cowork plugin context. In Hermes:
+
+- **If you have any structured financial-data MCP configured** (Hermes supports MCP — see `native-mcp` skill), prefer it for point-in-time comps, precedent transactions, and filings.
+- **Otherwise**, fall back to:
+  - `web_search` / `web_extract` against SEC EDGAR (`https://www.sec.gov/cgi-bin/browse-edgar`) for US filings
+  - Company IR pages for press releases, earnings decks
+  - `browser_navigate` for interactive data portals
+  - User-provided data (explicitly ask when the context doesn't have it)
+- **Never fabricate**. If a multiple, precedent, or filing number can't be sourced, flag the cell as `[UNSOURCED]` and surface it to the user.
+
+## Attribution
+
+This skill is adapted from Anthropic's Claude for Financial Services plugin suite (Apache-2.0). The Office-JS / Cowork live-Excel paths have been removed; this version targets headless openpyxl via the `excel-author` skill's conventions. Original: https://github.com/anthropics/financial-services
diff --git a/optional-skills/finance/merger-model/SKILL.md b/optional-skills/finance/merger-model/SKILL.md
new file mode 100644
index 0000000000..b2e2f88bc3
--- /dev/null
+++ b/optional-skills/finance/merger-model/SKILL.md
@@ -0,0 +1,143 @@
+---
+name: merger-model
+description: Build accretion/dilution (merger) models in Excel — pro-forma P&L, synergies, financing mix, EPS impact. Pairs with excel-author. Use for M&A pitches, board materials, or deal evaluation.
+version: 1.0.0
+author: Anthropic (adapted by Nous Research)
+license: Apache-2.0
+metadata:
+  hermes:
+    tags: [finance, m-and-a, merger, accretion-dilution, excel, openpyxl, modeling, investment-banking]
+    related_skills: [excel-author, pptx-author, dcf-model, 3-statement-model]
+---
+
+## Environment
+
+This skill assumes **headless openpyxl** — you are producing an .xlsx file on disk.
+Follow the `excel-author` skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables.
+Recalculate before delivery: `python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx`.
+
+# Merger Model
+
+Build accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms.
+
+## Workflow
+
+### Step 1: Gather Inputs
+
+**Acquirer:**
+- Company name, current share price, shares outstanding
+- LTM and NTM EPS (GAAP and adjusted)
+- P/E multiple
+- Pre-tax cost of debt, tax rate
+- Cash on balance sheet, existing debt
+
+**Target:**
+- Company name, current share price, shares outstanding (if public)
+- LTM and NTM EPS or net income
+- Enterprise value or equity value
+
+**Deal Terms:**
+- Offer price per share (or premium to current)
+- Consideration mix: % cash vs. % stock
+- New debt raised to fund cash portion
+- Expected synergies (revenue and cost) and phase-in timeline
+- Transaction fees and financing costs
+- Expected close date
+
+### Step 2: Purchase Price Analysis
+
+| Item | Value |
+|------|-------|
+| Offer price per share | |
+| Premium to current | |
+| Equity value | |
+| Plus: net debt assumed | |
+| Enterprise value | |
+| EV / EBITDA implied | |
+| P/E implied | |
+
+### Step 3: Sources & Uses
+
+| Sources | $ | Uses | $ |
+|---------|---|------|---|
+| New debt | | Equity purchase price | |
+| Cash on hand | | Refinance target debt | |
+| New equity issued | | Transaction fees | |
+| | | Financing fees | |
+| **Total** | | **Total** | |
+
+### Step 4: Pro Forma EPS (Accretion / Dilution)
+
+Calculate year-by-year (Year 1-3):
+
+| | Standalone | Pro Forma | Accretion/(Dilution) |
+|---|-----------|-----------|---------------------|
+| Acquirer net income | | | |
+| Target net income | | | |
+| Synergies (after tax) | | | |
+| Foregone interest on cash (after tax) | | | |
+| New debt interest (after tax) | | | |
+| Intangible amortization (after tax) | | | |
+| Pro forma net income | | | |
+| Pro forma shares | | | |
+| **Pro forma EPS** | | | |
+| **Accretion / (Dilution) %** | | | |
+
+### Step 5: Sensitivity Analysis
+
+**Accretion/Dilution vs. Synergies and Offer Premium:**
+
+| | $0M syn | $25M syn | $50M syn | $75M syn | $100M syn |
+|---|---------|----------|----------|----------|-----------|
+| 15% premium | | | | | |
+| 20% premium | | | | | |
+| 25% premium | | | | | |
+| 30% premium | | | | | |
+
+**Accretion/Dilution vs. Cash/Stock Mix:**
+
+| | 100% cash | 75/25 | 50/50 | 25/75 | 100% stock |
+|---|-----------|-------|-------|-------|------------|
+| Year 1 | | | | | |
+| Year 2 | | | | | |
+
+### Step 6: Breakeven Synergies
+
+Calculate the minimum synergies needed for the deal to be EPS-neutral in Year 1.
+
+### Step 7: Output
+
+- Excel workbook with:
+  - Assumptions tab
+  - Sources & uses
+  - Pro forma income statement
+  - Accretion/dilution summary
+  - Sensitivity tables
+  - Breakeven analysis
+- One-page merger consequences summary for pitch book
+
+## Important Notes
+
+- Always show both GAAP and adjusted (cash) EPS where relevant
+- Stock deals: use acquirer's current price for exchange ratio, note dilution from new shares
+- Include purchase price allocation — goodwill and intangible amortization matter for GAAP EPS
+- Synergy phase-in is critical — Year 1 is often only 25-50% of run-rate synergies
+- Don't forget foregone interest income on cash used and new interest expense on debt raised
+- Tax rate on synergies and interest adjustments should match the acquirer's marginal rate
+
+
+## Data sources — MCP first, web fallback
+
+Many passages below say "use the S&P Kensho MCP / Daloopa MCP / FactSet MCP". Those are commercial financial-data MCPs from the original Cowork plugin context. In Hermes:
+
+- **If you have any structured financial-data MCP configured** (Hermes supports MCP — see `native-mcp` skill), prefer it for point-in-time comps, precedent transactions, and filings.
+- **Otherwise**, fall back to:
+  - `web_search` / `web_extract` against SEC EDGAR (`https://www.sec.gov/cgi-bin/browse-edgar`) for US filings
+  - Company IR pages for press releases, earnings decks
+  - `browser_navigate` for interactive data portals
+  - User-provided data (explicitly ask when the context doesn't have it)
+- **Never fabricate**. If a multiple, precedent, or filing number can't be sourced, flag the cell as `[UNSOURCED]` and surface it to the user.
+
+## Attribution
+
+This skill is adapted from Anthropic's Claude for Financial Services plugin suite (Apache-2.0). The Office-JS / Cowork live-Excel paths have been removed; this version targets headless openpyxl via the `excel-author` skill's conventions. Original: https://github.com/anthropics/financial-services
diff --git a/optional-skills/finance/pptx-author/SKILL.md b/optional-skills/finance/pptx-author/SKILL.md
new file mode 100644
index 0000000000..b52f992975
--- /dev/null
+++ b/optional-skills/finance/pptx-author/SKILL.md
@@ -0,0 +1,172 @@
+---
+name: pptx-author
+description: Build PowerPoint decks headless with python-pptx. Pairs with excel-author for model-backed decks where every number traces to a workbook cell. Use for pitch decks, IC memos, earnings notes.
+version: 1.0.0
+author: Anthropic (adapted by Nous Research)
+license: Apache-2.0
+metadata:
+  hermes:
+    tags: [powerpoint, pptx, python-pptx, presentation, finance]
+    related_skills: [excel-author, powerpoint]
+---
+
+# pptx-author
+
+Produce a .pptx file on disk using `python-pptx`. Use when you need to deliver a deck as a file artifact, not drive a live PowerPoint session.
+
+Adapted from Anthropic's `pptx-author` and `pitch-deck` skills in [anthropics/financial-services](https://github.com/anthropics/financial-services). The MCP / Office-JS branches of the originals are dropped — this assumes headless Python.
+
+For the broader, already-shipped PowerPoint authoring skill (slides, speaker notes, embeds, media), see the built-in `powerpoint` skill. This skill is a lighter-weight pattern tuned for model-backed decks (pitch decks, IC memos, earnings notes) where every number must trace to a source workbook.
+
+## Output contract
+
+- Write to `./out/<name>.pptx`. Create `./out/` if it does not exist.
+- Return the relative path in your final message.
+
+## Setup
+
+```bash
+pip install "python-pptx>=0.6"
+```
+
+## Core conventions
+
+### One idea per slide
+Title states the takeaway; body supports it. A slide titled "Q3 Revenue" is weak; "Revenue growth accelerated to 14% Y/Y in Q3" is strong.
+
+### Every number traces to the model
+If a figure on a slide came from `./out/model.xlsx`, footnote the sheet and cell.
+
+```
+Revenue: $1,250M  (Source: model.xlsx, Inputs!C3)
+```
+
+Never transcribe numbers from memory or from a summary — open the workbook, read the named range, and bind the deck value to it programmatically when you can.
+
+### Use the firm template when one is mounted
+If `./templates/firm-template.pptx` exists, load it so the deck inherits branded colors, fonts, and master layouts.
+
+```python
+from pptx import Presentation
+from pathlib import Path
+
+template = Path("./templates/firm-template.pptx")
+prs = Presentation(str(template)) if template.exists() else Presentation()
+```
+
+### Charts: PNG-from-model beats native pptx charts
+When fidelity matters (the model's chart styling must match the deck exactly), render the chart to PNG from the source workbook and embed the image. Native `pptx.chart` charts are fragile and often don't match firm conventions.
+
+```python
+from pptx.util import Inches
+slide.shapes.add_picture("./out/charts/football_field.png",
+                         Inches(1), Inches(2),
+                         width=Inches(8))
+```
+
+### No external sends
+This skill writes a file. It never emails, uploads, or posts. Orchestration layers handle delivery.
+
+## Skeleton
+
+```python
+from pptx import Presentation
+from pptx.util import Inches, Pt
+from pptx.dml.color import RGBColor
+from pathlib import Path
+
+template = Path("./templates/firm-template.pptx")
+prs = Presentation(str(template)) if template.exists() else Presentation()
+
+# Title slide
+slide = prs.slides.add_slide(prs.slide_layouts[0])
+slide.shapes.title.text = "Project Aurora — Strategic Alternatives"
+slide.placeholders[1].text = "Preliminary Discussion Materials"
+
+# Valuation summary slide (title-only layout)
+slide = prs.slides.add_slide(prs.slide_layouts[5])
+slide.shapes.title.text = "Valuation implies $38–$52 per share across methodologies"
+
+# Add a table bound to model outputs
+rows, cols = 5, 4
+tbl_shape = slide.shapes.add_table(rows, cols,
+                                   Inches(0.5), Inches(1.5),
+                                   Inches(9), Inches(3))
+tbl = tbl_shape.table
+headers = ["Methodology", "Low ($)", "Mid ($)", "High ($)"]
+for c, h in enumerate(headers):
+    tbl.cell(0, c).text = h
+
+# In a real deck, read these from the model workbook with openpyxl
+data = [
+    ("Trading comps",     "35", "41", "48"),
+    ("Precedent M&A",     "39", "45", "52"),
+    ("DCF (base)",        "36", "43", "51"),
+    ("LBO (10% IRR)",     "33", "38", "44"),
+]
+for r, row in enumerate(data, start=1):
+    for c, val in enumerate(row):
+        tbl.cell(r, c).text = val
+
+# Embed a chart rendered from the model
+slide = prs.slides.add_slide(prs.slide_layouts[5])
+slide.shapes.title.text = "Football field — current price $42"
+slide.shapes.add_picture("./out/charts/football_field.png",
+                         Inches(1), Inches(1.8), width=Inches(8))
+
+Path("./out").mkdir(exist_ok=True)
+prs.save("./out/pitch-aurora.pptx")
+```
+
+## Binding deck numbers to the source workbook
+
+Read named ranges or specific cells from your Excel model so deck numbers never drift.
+
+```python
+from openpyxl import load_workbook
+
+wb = load_workbook("./out/model.xlsx", data_only=True)
+def nr(name):
+    """Resolve a named range to its current computed value."""
+    rng = wb.defined_names[name]
+    sheet, coord = next(rng.destinations)
+    return wb[sheet][coord].value
+
+revenue_fy24 = nr("RevenueFY24")
+implied_mid  = nr("ImpliedSharePriceBase")
+```
+
+Then build deck content using those values:
+```python
+slide.shapes.title.text = f"Implied share price of ${implied_mid:.2f} (base case)"
+```
+
+Remember to recalculate the workbook before reading it — openpyxl only sees computed values if something has already calculated the sheet. Run the recalc helper in the `excel-author` skill first, or open/save through a real Excel session.
+
+## Slide-type checklist for pitch decks
+
+A typical banking pitch deck follows this structure. Not prescriptive, but useful as a starting skeleton:
+
+1. Cover / title
+2. Disclaimer
+3. Table of contents
+4. Situation overview
+5. Company snapshot (the target)
+6. Market / sector context
+7. Valuation summary (football field) — the money slide
+8. Trading comps detail
+9. Precedent transactions detail
+10. DCF summary
+11. Illustrative LBO / sponsor case
+12. Process considerations
+13. Appendix
+
+## When NOT to use this skill
+
+- Users in a live PowerPoint session with an Office MCP available — drive their live doc instead.
+- Non-financial slideware (quarterly all-hands, marketing decks) — use the broader `powerpoint` skill.
+- Decks with heavy animation, transitions, or speaker notes — use the broader `powerpoint` skill.
+
+## Attribution
+
+Conventions adapted from Anthropic's Claude for Financial Services plugin suite, Apache-2.0 licensed. Original: https://github.com/anthropics/financial-services/tree/main/plugins/agent-plugins/pitch-agent/skills/pptx-author