Workbook Doctor

Workbook Doctor

Performs a structured audit of a workbook before it drives decisions. AI tools generate clean-looking spreadsheets that frequently contain broken formula logic, hardcoded outputs masquerading as live calculations, and assumptions never labeled as such. This skill runs four diagnostic passes and produces a clear verdict: safe to use, needs repair, or do not use.

When to Invoke

Trigger on: "workbook-doctor", "audit this spreadsheet", "check my Excel", "verify my workbook", "are my formulas right", "is this model safe to use", "QA my financial model", "check before I share this", or any time the user is about to use an AI-generated workbook for a consequential decision.

Phase 1: Workbook Map

Before evaluating formulas, build a structural map of the workbook.

For each sheet, identify and document:

Sheet: [name]
Purpose: [what this sheet does]
Inputs (assumption cells): [list key variable cells and their current values]
Outputs (result cells): [list key output cells and their values]
Dependencies: [which other sheets does this sheet pull from?]
Hardcoded regions: [areas that appear to be manually entered rather than formula-driven]

Ask the user to paste or describe the workbook structure if direct file access is unavailable. The map does not need to be exhaustive — cover every sheet that drives a key output.

Phase 2: Formula Risk Scan

Run each check below on the formulas and structure identified in Phase 1. For each finding, record: sheet name, cell reference (if known), finding description, and severity.

Check 1 — Formula Consistency

• Are formulas consistent across rows in the same column, or do some rows have different formula logic?
• Are there cells in formula areas that contain plain numbers instead of formulas?
• Do SUM ranges cover all rows they should, or do some stop short?

Check 2 — Live vs. Hardcoded Outputs

• When input assumption cells change, do output cells change accordingly?
• Are any "calculated" cells actually hardcoded constants that will never update?
• Are there cells formatted to look like formulas but containing static values?

Check 3 — Circular References

• Are there circular dependencies between cells?
• Does the workbook rely on iterative calculation to resolve them?

Check 4 — Reference Integrity

• Do formulas reference cells that exist, or are there broken references (#REF! errors)?
• Do cross-sheet references point to the correct sheet and range?
• Are there named ranges that have been deleted but are still referenced?

Check 5 — Aggregation Accuracy

• Do summary totals equal the sum of their detail rows?
• Do percentages calculated from subtotals match independently calculated percentages?
• Are there rounding differences that accumulate to material discrepancies?

Check 6 — Stale Data

• Are there hardcoded dates, prices, or rates that are unlikely to have been updated?
• Does the workbook reference external data (market rates, FX, headcount) that may be out of date?

Phase 3: Repair Plan

For each finding from Phase 2, classify and recommend an action:

Finding [F01]:
  Sheet / Cell: [location]
  Issue: [description]
  Severity: must-fix / should-fix / optional
  Recommended action: [specific fix]
  Verification method: [how to confirm the fix worked]

Severity definitions:

• Must-fix: the workbook will produce materially wrong outputs if this is not corrected. Do not use until resolved.
• Should-fix: the workbook may produce correct results now but is brittle or misleading. Fix before sharing.
• Optional: cosmetic or low-risk. Fix at your discretion.

Phase 4: Verification Memo

Issue a final verdict on four dimensions:

## Workbook Verification Memo

Workbook: [name]
Audited: [date]

### Formula Consistency
Status: PASS / FAIL / CONDITIONAL
Notes: [key findings or "formulas consistent across all reviewed ranges"]

### Source Traceability
Status: PASS / FAIL / CONDITIONAL
Notes: [key findings or "all input figures traced to identified sources"]

### Assumption Clarity
Status: PASS / FAIL / CONDITIONAL
Notes: [key findings or "assumption cells clearly labeled and separated from outputs"]

### Data Freshness
Status: PASS / FAIL / CONDITIONAL
Notes: [key findings or "all data verified current as of [date]"]

---

Overall verdict: SAFE TO USE / CONDITIONAL USE / DO NOT USE

Conditions (if CONDITIONAL): [list what must be resolved before use]
Open items (if DO NOT USE): [list must-fix items blocking use]

PASS: no issues found in this dimension. CONDITIONAL: issues exist but do not block use if the stated conditions are met. FAIL: issues block use of this workbook for any consequential decision.

Verification

• All six formula risk checks run — none skipped
• Every finding has a location, not just a category
• Repair plan includes verification method for each must-fix item
• Verification memo issued with explicit overall verdict
• User informed of any must-fix items before they use the workbook

Source

Nate Jones newsletter (2026-05-27) — "The deck got forwarded with a wrong number inside. The Trust Layer's two-model review is built to catch exactly that." The workbook doctor implements the Trust Layer Guide's Prompt Kit 1 (Workbook Doctor). Core insight: AI-generated spreadsheets look correct but frequently have hardcoded outputs that do not respond to changed assumptions — the formula risk scan is the only reliable way to catch this without running every scenario manually.