Xlsx Toolkit

Audit .xlsx files using the standard library only — no openpyxl required. Reads OOXML directly via zipfile + xml.etree.

Table of Contents

• Keywords
• Quick Start
• Core Workflows
• Tools
• Reference Guides
• Templates
• Best Practices

Keywords

xlsx, Excel, spreadsheet, workbook, financial model, formula audit, hidden sheets, external references, named ranges, data validation

Quick Start

python scripts/xlsx_auditor.py model.xlsx

Outputs: sheet count and names, hidden-sheet count, cell count per sheet, formula count per sheet, external link count, named range count, data validation rule count.

Core Workflows

Workflow 1: Pre-Send Workbook Audit

Goal: Catch the issues that embarrass the sender — leftover hidden sheets, broken external links, unused named ranges, formulas referencing local file paths.

Steps:

1. Run audit
2. Hidden sheets > 0 → confirm intentional or delete
3. External links > 0 → verify links point to public / shared sources, not your local drive
4. Named-range count anomalies (very high) → likely cruft from prior model versions; clean up
5. Re-run until clean

Time Estimate: 5-10 minutes per workbook.

Workflow 2: Financial Model Review

Goal: Quantify the rough complexity of a financial model before reading cell-by-cell.

Steps:

1. Run audit; capture per-sheet cell counts and formula counts
2. Sheets with formula density > 70% are calculation sheets; should be well-structured
3. Sheets with formula density 0-10% are inputs; should be obviously labeled
4. Sheets with formula density 10-70% are mixed — easiest place for errors to hide
5. Cross-reference with references/financial_model_audit_guide.md

Time Estimate: 30-60 minutes per model audit (audit + targeted reading).

Workflow 3: Workbook Handoff Check

Goal: Ensure a workbook handed off to another team or partner won't break on their machine.

Steps:

1. Run audit
2. External links → re-link to shared paths (OneDrive, SharePoint, S3) or hard-code values
3. Custom named ranges → document if recipient is expected to extend; remove if internal
4. Macros (xlsm) → audit shows non-.xlsx extension expected; convert if recipient cannot run macros
5. File size > 10 MB → consider splitting or removing image / chart blobs

Time Estimate: 10-20 minutes per workbook.

Tools

xlsx_auditor.py

Reads a .xlsx file as a ZIP archive and parses OOXML directly.

python scripts/xlsx_auditor.py model.xlsx
python scripts/xlsx_auditor.py model.xlsx --json

Reports:

• Sheet list with name, hidden status, cell count, formula count, formula density %
• Total cell and formula counts
• Named ranges and their scopes
• External link references (file paths or URLs)
• Data validation rule count
• File size

Limits:

• Does not evaluate formulas. To check whether formulas are correct, use Excel itself or a financial-model-checker library.
• Does not read cell values for non-shared-string cells beyond counting; full value extraction requires more parsing than this tool does.

Reference Guides

• references/financial_model_audit_guide.md — Patterns for auditing financial models; common error categories; defensive structure tips

Templates

• assets/workbook_handoff_checklist.md — Pre-send xlsx sign-off checklist

Best Practices

• Hide internal-only sheets only when intended. If a sheet is hidden because it's WIP, delete it before sending.
• Avoid external links across handoffs. A formula referencing 'C:\Users\you\Desktop\old-model.xlsx' is the workbook equivalent of leaving your laptop name in the document author field.
• Name your inputs. Cells like Inputs!B7 mean nothing. Named ranges like WACC and RevenueGrowth survive structural changes.
• One model, one purpose. Workbooks that calculate, present, and serve as a database of records always end up broken.

Integration Points

• Pairs with finance/ skills for financial-model review
• Pairs with c-level-advisor/cfo-advisor for board-pack workbook review
• Used by data-analytics/ for ad-hoc analytics handoff