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title: "Excel Author"
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sidebar_label: "Excel Author"
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description: "Build auditable Excel workbooks headless with openpyxl — blue/black/green cell conventions, formulas over hardcodes, named ranges, balance checks, sensitivit..."
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---
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{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
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# Excel Author
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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.
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## Skill metadata
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| Source | Optional — install with `hermes skills install official/finance/excel-author` |
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| Path | `optional-skills/finance/excel-author` |
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| Version | `1.0.0` |
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| Author | Anthropic (adapted by Nous Research) |
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| License | Apache-2.0 |
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| Platforms | linux, macos, windows |
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| Tags | `excel`, `openpyxl`, `finance`, `spreadsheet`, `modeling` |
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| Related skills | [`pptx-author`](/docs/user-guide/skills/optional/finance/finance-pptx-author), [`dcf-model`](/docs/user-guide/skills/optional/finance/finance-dcf-model), [`comps-analysis`](/docs/user-guide/skills/optional/finance/finance-comps-analysis), [`lbo-model`](/docs/user-guide/skills/optional/finance/finance-lbo-model), [`3-statement-model`](/docs/user-guide/skills/optional/finance/finance-3-statement-model) |
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## Reference: full SKILL.md
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:::info
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The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.
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:::
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# excel-author
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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.
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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.
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## Output contract
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- Write to `./out/<name>.xlsx`. Create `./out/` if it does not exist.
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- Return the relative path in your final message so downstream tools can pick it up.
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- One logical model per file. Do not append to an existing workbook unless explicitly asked.
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## Setup
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```bash
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pip install "openpyxl>=3.0"
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```
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## Core conventions (non-negotiable)
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### Blue / black / green cell color
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- **Blue** (`Font(color="0000FF")`) — hardcoded input a human entered. Revenue drivers, WACC inputs, terminal growth, market data.
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- **Black** (default) — formula. Every derived cell is a live Excel formula.
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- **Green** (`Font(color="006100")`) — link to another sheet or external file.
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A reviewer can then scan the sheet and immediately see what's an assumption vs. what's computed.
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### Formulas over hardcodes
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Every calculation cell MUST be a formula string, never a number computed in Python and pasted as a value.
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```python
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# WRONG — silent bug waiting to happen
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ws["D20"] = revenue_prior_year * (1 + growth)
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# CORRECT — flexes when the user changes the assumption
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ws["D20"] = "=D19*(1+$B$8)"
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```
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The only hardcoded numbers permitted:
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1. Raw historical inputs (actual revenues, reported EBITDA, etc.)
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2. Assumption drivers the user is meant to flex (growth rates, WACC inputs, terminal g)
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3. Current market data (share price, debt balance) — with a cell comment documenting source + date
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If you catch yourself computing a value in Python and writing the result, stop.
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### Named ranges for cross-sheet references
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Use named ranges for any figure referenced from another sheet, a deck, or a memo.
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```python
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from openpyxl.workbook.defined_name import DefinedName
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wb.defined_names["WACC"] = DefinedName("WACC", attr_text="Inputs!$C$8")
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# then elsewhere:
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calc["D30"] = "=D29/WACC"
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```
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### Balance checks tab
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Include a `Checks` tab that ties everything and surfaces TRUE/FALSE:
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- Balance sheet balances (assets = liabilities + equity)
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- Cash flow ties to period-over-period cash change on the BS
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- Sum-of-parts ties to consolidated totals
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- No rogue hardcodes inside calc ranges
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Example:
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```python
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checks = wb.create_sheet("Checks")
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checks["A2"] = "BS balances"
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checks["B2"] = "=IS!D20-IS!D21-IS!D22"
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checks["C2"] = "=ABS(B2)<0.01" # TRUE/FALSE
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```
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### Cell comments on every hardcoded input
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Add the comment AS you create the cell, not later.
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```python
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from openpyxl.comments import Comment
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ws["C2"] = 1_250_000_000
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ws["C2"].font = Font(color="0000FF")
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ws["C2"].comment = Comment("Source: 10-K FY2024, p.47, revenue line", "analyst")
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```
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Format: `Source: [System/Document], [Date], [Reference], [URL if applicable]`.
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Never defer sourcing. Never write `TODO: add source`.
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## Skeleton: typical financial model
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```python
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from openpyxl import Workbook
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from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
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from openpyxl.comments import Comment
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from openpyxl.utils import get_column_letter
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from pathlib import Path
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BLUE = Font(color="0000FF")
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BLACK = Font(color="000000")
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GREEN = Font(color="006100")
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BOLD = Font(bold=True)
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HEADER_FILL = PatternFill("solid", fgColor="1F4E79")
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HEADER_FONT = Font(color="FFFFFF", bold=True)
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wb = Workbook()
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# --- Inputs tab ---
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inp = wb.active
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inp.title = "Inputs"
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inp["A1"] = "MARKET DATA & KEY INPUTS"
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inp["A1"].font = HEADER_FONT
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inp["A1"].fill = HEADER_FILL
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inp.merge_cells("A1:C1")
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inp["B3"] = "Revenue FY2024"
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inp["C3"] = 1_250_000_000
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inp["C3"].font = BLUE
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inp["C3"].comment = Comment("Source: 10-K FY2024 p.47", "model")
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inp["B4"] = "Growth Rate"
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inp["C4"] = 0.12
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inp["C4"].font = BLUE
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# --- Calc tab ---
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calc = wb.create_sheet("DCF")
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calc["B2"] = "Projected Revenue"
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calc["C2"] = "=Inputs!C3*(1+Inputs!C4)" # formula, black
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# --- Checks tab ---
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chk = wb.create_sheet("Checks")
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chk["A2"] = "BS balances"
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chk["B2"] = "=ABS(BS!D20-BS!D21-BS!D22)<0.01"
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Path("./out").mkdir(exist_ok=True)
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wb.save("./out/model.xlsx")
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```
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## Section headers with merged cells
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openpyxl quirk: when you merge, set the value on the top-left cell and style the full range separately.
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```python
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ws["A7"] = "CASH FLOW PROJECTION"
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ws["A7"].font = HEADER_FONT
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ws.merge_cells("A7:H7")
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for col in range(1, 9): # A..H
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ws.cell(row=7, column=col).fill = HEADER_FILL
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```
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## Sensitivity tables
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Build with loops, not hardcoded formulas per cell. Rules:
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- **Odd number of rows/cols** (5×5 or 7×7) — guarantees a true center cell.
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- **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.
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- **Highlight the center cell** with medium-blue fill (`"BDD7EE"`) and bold.
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- Populate every cell with a full recalculation formula — never an approximation.
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```python
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# 5x5 WACC (rows) x terminal growth (cols) sensitivity
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wacc_axis = [0.08, 0.085, 0.09, 0.095, 0.10] # center row = base 9.0%
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term_axis = [0.02, 0.025, 0.03, 0.035, 0.04] # center col = base 3.0%
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start_row = 40
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ws.cell(row=start_row, column=1).value = "Implied Share Price ($)"
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ws.cell(row=start_row, column=1).font = BOLD
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for j, g in enumerate(term_axis):
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ws.cell(row=start_row+1, column=2+j).value = g
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ws.cell(row=start_row+1, column=2+j).font = BLUE
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for i, w in enumerate(wacc_axis):
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r = start_row + 2 + i
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ws.cell(row=r, column=1).value = w
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ws.cell(row=r, column=1).font = BLUE
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for j, g in enumerate(term_axis):
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c = 2 + j
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# Full DCF recalc formula (simplified for illustration).
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# In a real model this references the full projection block.
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ws.cell(row=r, column=c).value = (
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f"=SUMPRODUCT(FCF_range,1/(1+{w})^year_offset) + "
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f"FCF_terminal*(1+{g})/({w}-{g})/(1+{w})^terminal_year"
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)
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# Highlight center cell (base case)
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center = ws.cell(row=start_row+2+len(wacc_axis)//2,
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column=2+len(term_axis)//2)
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center.fill = PatternFill("solid", fgColor="BDD7EE")
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center.font = BOLD
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```
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## Recalculating before delivery
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openpyxl writes formula strings but does not compute them. Excel recalculates on open, but downstream consumers (auto-check scripts, CI) need computed values.
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Run LibreOffice or a dedicated recalc step before delivery:
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```bash
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# LibreOffice headless recalc
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libreoffice --headless --calc --convert-to xlsx ./out/model.xlsx --outdir ./out/
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```
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Or use a Python recalc helper (see `scripts/recalc.py` in this skill).
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## Model layout planning
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Before writing any formula:
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1. Define ALL section row positions
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2. Write ALL headers and labels
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3. Write ALL section dividers and blank rows
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4. THEN write formulas using the locked row positions
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This prevents the cascading-formula-breakage pattern where inserting a header row after formulas are written shifts every downstream reference.
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## Verify step-by-step with the user
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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.
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Checkpoint pattern:
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- After Inputs block → show raw inputs, confirm before projecting
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- After Revenue projections → confirm top line + growth
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- After FCF build → confirm the full schedule
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- After WACC → confirm inputs
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- After valuation → confirm the equity bridge
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- THEN build sensitivity tables
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## When NOT to use this skill
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- Users in a live Excel session with an Office MCP available — drive their live workbook instead.
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- Pure tabular data export with no formulas — `csv` or `pandas.to_excel` is simpler.
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- Dashboards / charts with heavy interactivity — use a real BI tool.
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## Attribution
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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
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