Skills afrexai-spreadsheet-engineering
Spreadsheet Engineering — AfrexAI
install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/1kalin/afrexai-spreadsheet-engineering" ~/.claude/skills/openclaw-skills-afrexai-spreadsheet-engineering && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/1kalin/afrexai-spreadsheet-engineering" ~/.openclaw/skills/openclaw-skills-afrexai-spreadsheet-engineering && rm -rf "$T"
manifest:
skills/1kalin/afrexai-spreadsheet-engineering/SKILL.mdsource content
Spreadsheet Engineering — AfrexAI
Build bulletproof spreadsheets: financial models, dashboards, data systems, and automation. Platform-agnostic methodology for Google Sheets, Excel, and LibreOffice.
Quick Health Check
Score your spreadsheet /16:
| Signal | Healthy | Sick |
|---|---|---|
| Named ranges for all key inputs | ✅ Uses named ranges | ❌ Raw cell references everywhere |
| Inputs separated from calculations | ✅ Clear input section | ❌ Hardcoded values in formulas |
| No circular references | ✅ Clean dependency chain | ❌ Iterative calculation warnings |
| Documentation/comments exist | ✅ README sheet + cell notes | ❌ "What does this formula do?" |
| Error handling in formulas | ✅ IFERROR/IFNA wrapping | ❌ #REF! #N/A scattered everywhere |
| Consistent formatting | ✅ Style guide followed | ❌ Random fonts, colors, sizes |
| Version history/backup | ✅ Named versions + changelog | ❌ "Final_v3_REAL_final.xlsx" |
| Data validation on inputs | ✅ Dropdowns + range constraints | ❌ Free-text in structured fields |
Score: 0-4 🔴 rebuild | 5-8 🟡 refactor | 9-12 🟢 optimize | 13-16 🔵 production-grade
Phase 1: Architecture & Planning
Spreadsheet Strategy Brief
spreadsheet_brief: name: "[Descriptive Name]" purpose: "[What decision does this support?]" owner: "[Who maintains this]" audience: "[Who uses this — technical level]" update_frequency: "[Real-time / Daily / Weekly / Monthly / Ad-hoc]" data_sources: - source: "[Where data comes from]" method: "[Manual / Import / API / IMPORTRANGE / Power Query]" refresh: "[How often]" outputs: - "[Dashboard / Report / Export / Decision support]" complexity_tier: "[Simple / Standard / Complex / Enterprise]" platform: "[Google Sheets / Excel / Both]" kill_criteria: - "If >50 users need simultaneous editing → move to database" - "If >100K rows → move to database or BI tool" - "If requires audit trail → move to proper system"
Complexity Tier Guide
| Tier | Rows | Sheets | Users | Formulas | Example |
|---|---|---|---|---|---|
| Simple | <1K | 1-3 | 1-3 | Basic | Budget tracker, checklist |
| Standard | 1K-10K | 3-8 | 3-10 | Intermediate | Financial model, project tracker |
| Complex | 10K-50K | 8-15 | 10-30 | Advanced | Multi-dept dashboard, CRM |
| Enterprise | 50K+ | 15+ | 30+ | Expert | Data warehouse substitute (🚩 migrate) |
When NOT to Use a Spreadsheet
| Scenario | Better Tool |
|---|---|
| >100K rows of data | Database (PostgreSQL, SQLite) |
| >10 concurrent editors | Web app or Airtable |
| Complex relational data (3+ entity types) | Database + app |
| Needs audit trail / compliance | Purpose-built system |
| Real-time data processing | ETL pipeline + BI tool |
| Version-controlled code logic | Actual code (Python, JS) |
Rule: Spreadsheets are prototyping tools that become production systems by accident. Know when to graduate.
Phase 2: Sheet Architecture
Recommended Structure
📊 Workbook ├── 📋 README — Purpose, instructions, changelog ├── 📊 Dashboard — Charts, KPIs, summary (output only) ├── ⚙️ Config — Settings, parameters, dropdowns ├── 📥 Data_Input — Raw data entry or imports ├── 🔧 Calculations — All formulas and transformations ├── 📈 Analysis — Pivot tables, scenarios, what-if ├── 📤 Output — Formatted reports for export/print └── 🗄️ Reference — Lookup tables, constants, mappings
7 Architecture Rules
- One direction of flow — Data flows left→right or top→bottom. Never circular.
- Inputs separate from calculations — NEVER hardcode numbers in formulas. Use named ranges.
- One fact in one place — If a value is used in 3 places, define it once and reference it.
- Color code by purpose — Blue = input, Black = formula, Green = linked from other sheet, Red = warning.
- Freeze panes on every data sheet — Header row and label columns always visible.
- Protect formula cells — Lock everything except input cells. Prevent accidental overwrites.
- README sheet is mandatory — Every workbook starts with purpose, instructions, and changelog.
Naming Conventions
Sheets: PascalCase — Dashboard, Raw_Data, Config Named Ranges: SCREAMING_SNAKE — TAX_RATE, START_DATE, REVENUE_TARGET Tabs: Prefix with emoji or number for sort order — 01_Dashboard, 02_Config Files: YYYY-MM-DD_Description_vX.xlsx
Color Coding Standard
| Color | Meaning | When to Use |
|---|---|---|
| 🔵 Light blue background | User input cell | Editable fields |
| ⬛ Black text | Formula/calculated | Auto-populated cells |
| 🟢 Green text | Linked from other sheet | Cross-sheet references |
| 🔴 Red text/background | Warning/error | Validation failures, negative values |
| 🟡 Yellow background | Assumption | Key assumptions that drive the model |
| ⬜ Grey background | Reference/locked | Constants, lookup tables |
Phase 3: Formula Engineering
Formula Complexity Levels
| Level | Techniques | Example |
|---|---|---|
| L1 Basic | SUM, AVERAGE, COUNT, IF, CONCATENATE | |
| L2 Intermediate | VLOOKUP/XLOOKUP, SUMIFS, INDEX/MATCH, TEXT | |
| L3 Advanced | ARRAYFORMULA, QUERY, INDIRECT, nested IFs | |
| L4 Expert | LAMBDA, MAP/REDUCE, LET, dynamic arrays, MAKEARRAY | |
Essential Formula Patterns
Lookup — Always Prefer XLOOKUP/INDEX-MATCH Over VLOOKUP
❌ VLOOKUP (fragile — breaks when columns inserted): =VLOOKUP(A2, Data!A:D, 4, FALSE) ✅ XLOOKUP (Excel 365 / Google Sheets): =XLOOKUP(A2, Data!A:A, Data!D:D, "Not Found") ✅ INDEX/MATCH (universal — works everywhere): =INDEX(Data!D:D, MATCH(A2, Data!A:A, 0))
Multi-Criteria Lookup
=XLOOKUP(1, (Data!A:A=B2)*(Data!B:B=C2), Data!D:D, "Not Found") Or INDEX/MATCH array (Ctrl+Shift+Enter in older Excel): =INDEX(Data!D:D, MATCH(1, (Data!A:A=B2)*(Data!B:B=C2), 0))
Conditional Aggregation
Single condition: =SUMIF(Category, "Sales", Amount) Multiple conditions: =SUMIFS(Amount, Category, "Sales", Region, "US", Date, ">="&DATE(2025,1,1)) Count with conditions: =COUNTIFS(Status, "Active", Score, ">80") Average with conditions: =AVERAGEIFS(Score, Department, "Engineering", Status, "Active")
Date Calculations
Working days between dates: =NETWORKDAYS(Start, End, Holidays) Add working days: =WORKDAY(Start, 10, Holidays) Month-end date: =EOMONTH(A2, 0) Quarter from date: =ROUNDUP(MONTH(A2)/3, 0) Fiscal year (Apr-Mar): =IF(MONTH(A2)>=4, YEAR(A2), YEAR(A2)-1)
Text Manipulation
Extract domain from email: =MID(A2, FIND("@",A2)+1, LEN(A2)) Proper case with exceptions: =PROPER(SUBSTITUTE(LOWER(A2)," llc"," LLC")) Clean messy data: =TRIM(CLEAN(SUBSTITUTE(A2, CHAR(160), " ")))
Dynamic Arrays (Excel 365 / Google Sheets)
FILTER: =FILTER(Data, Data[Status]="Active", Data[Amount]>1000) SORT: =SORT(FILTER(Data, Data[Region]="US"), 3, -1) UNIQUE: =UNIQUE(Data[Category]) SEQUENCE: =SEQUENCE(12, 1, DATE(2025,1,1), 30) — 12 monthly dates
Google Sheets QUERY (Power Feature)
Basic aggregation: =QUERY(Data!A:F, "SELECT A, SUM(F) WHERE B='Active' GROUP BY A ORDER BY SUM(F) DESC LABEL SUM(F) 'Total Revenue'") Date filtering: =QUERY(Data!A:F, "SELECT A, B, F WHERE C >= date '"&TEXT(B1,"yyyy-MM-dd")&"' ORDER BY F DESC LIMIT 10") Pivot-style: =QUERY(Data!A:F, "SELECT A, SUM(F) GROUP BY A PIVOT B")
LET for Readable Complex Formulas
=LET( revenue, SUMIFS(Sales!D:D, Sales!A:A, A2), costs, SUMIFS(Costs!D:D, Costs!A:A, A2), margin, (revenue - costs) / revenue, IF(revenue=0, "No Data", IF(margin > 0.3, "✅ Healthy", IF(margin > 0.1, "⚠️ Watch", "🔴 Critical"))) )
LAMBDA (Custom Functions)
Named LAMBDA (define in Name Manager / named ranges): FISCAL_QUARTER = LAMBDA(date, "FY"&IF(MONTH(date)>=4,YEAR(date),YEAR(date)-1)&" Q"&ROUNDUP(MOD(MONTH(date)+8,12)/3,0)) MAP with LAMBDA: =MAP(A2:A100, LAMBDA(x, PROPER(TRIM(x))))
10 Formula Rules
- NEVER hardcode values — Use named ranges or a Config sheet
- Wrap external lookups in IFERROR —
=IFERROR(XLOOKUP(...), "Not Found") - Use LET for formulas >100 chars — Readable, debuggable, faster
- Prefer XLOOKUP over VLOOKUP — More flexible, no column counting
- One formula per cell — Don't nest 5+ functions. Break into helper columns.
- Comment complex formulas — Use cell notes or a documentation column
- Test with edge cases — Empty cells, zeros, dates before 1900, text in number fields
- Avoid INDIRECT for performance — It's volatile (recalculates every time)
- Use structured references in tables —
not=SUM(Table1[Amount])=SUM(D:D) - Keep formulas auditable — Someone else (or future you) must understand them
Phase 4: Data Validation & Quality
Input Validation Checklist
| Data Type | Validation | Implementation |
|---|---|---|
| Date | Date range | Data validation: between START and END |
| Currency | Number ≥ 0 | Data validation: decimal ≥ 0, format $#,##0.00 |
| Percentage | 0-100 or 0-1 | Data validation: decimal between 0 and 1 |
| Category | Dropdown list | Data validation: list from Reference sheet |
| Contains @ | Custom: | |
| Phone | Length check | Custom: |
| Required field | Not blank | Custom: |
| ID/Code | Unique + format | Custom: |
Data Cleaning Pipeline
Step 1: Remove whitespace =TRIM(CLEAN(A2)) Step 2: Standardize case =PROPER(A2) or =UPPER(A2) Step 3: Remove duplicates Use Remove Duplicates tool or UNIQUE() Step 4: Fix dates =DATEVALUE(TEXT(A2,"YYYY-MM-DD")) Step 5: Validate =IF(AND(A2>0, A2<1000000, ISNUMBER(A2)), "✅", "❌ Check")
Conditional Formatting Rules (Priority Order)
- 🔴 Errors — Any cell with #REF!, #N/A, #VALUE! → Red background
- 🟡 Warnings — Values outside expected range → Yellow background
- 🟢 Positive — On-target metrics → Green text
- 📊 Data bars — Numeric ranges → Proportional bars
- 🎯 Icons — Status indicators → Traffic light icon sets
Phase 5: Financial Modeling
Model Architecture
📊 Financial Model ├── 📋 Cover — Model name, version, date, author ├── ⚙️ Assumptions — ALL inputs here (blue cells), scenarios ├── 📊 Revenue — Revenue build-up by product/segment ├── 📊 COGS — Cost of goods/services ├── 📊 OpEx — Operating expenses by category ├── 📊 P&L — Income statement (auto-calculated) ├── 📊 Balance_Sheet — Assets, liabilities, equity ├── 📊 Cash_Flow — Operating, investing, financing ├── 📈 DCF — Discounted cash flow valuation ├── 📈 Scenarios — Bull/Base/Bear cases ├── 📊 KPIs — Key metrics dashboard └── 📊 Charts — Visualizations
Revenue Model Patterns
saas_revenue: mrr_start: "=PREVIOUS_MONTH_MRR" new_mrr: "=NEW_CUSTOMERS * ARPU" expansion_mrr: "=EXISTING * EXPANSION_RATE / 12" contraction_mrr: "=EXISTING * CONTRACTION_RATE / 12" churn_mrr: "=EXISTING * CHURN_RATE / 12" mrr_end: "=MRR_START + NEW + EXPANSION - CONTRACTION - CHURN" arr: "=MRR_END * 12" unit_economics: cac: "=TOTAL_SALES_MARKETING / NEW_CUSTOMERS" ltv: "=ARPU / MONTHLY_CHURN_RATE" ltv_cac_ratio: "=LTV / CAC # Target: >3.0" cac_payback_months: "=CAC / ARPU # Target: <12"
Scenario Analysis Template
=SWITCH(SCENARIO_SELECTOR, "Bull", Assumptions!B2 * 1.3, "Base", Assumptions!B2, "Bear", Assumptions!B2 * 0.7, Assumptions!B2) Or with CHOOSE: =CHOOSE(SCENARIO_INDEX, BEAR_VALUE, BASE_VALUE, BULL_VALUE)
Sensitivity Analysis (Data Table)
Two-variable data table: - Row input: Growth Rate (10%, 15%, 20%, 25%, 30%) - Column input: Churn Rate (2%, 3%, 5%, 7%, 10%) - Output cell: NPV or IRR - Select range → Data → What-If Analysis → Data Table
Common Financial Formulas
NPV: =NPV(DISCOUNT_RATE, CF1:CF10) + INITIAL_INVESTMENT IRR: =IRR(CF_RANGE, guess) XIRR: =XIRR(CF_VALUES, CF_DATES) — irregular cash flows PMT: =PMT(RATE/12, NPER*12, -PV) — loan payment Compound growth: =FV * (1 + RATE)^YEARS CAGR: =(END_VALUE/START_VALUE)^(1/YEARS) - 1 Break-even units: =FIXED_COSTS / (PRICE - VARIABLE_COST)
Phase 6: Dashboard Design
Dashboard Layout
┌─────────────────────────────────────────────────┐ │ 📊 Dashboard Title Period: [Dropdown] │ │ Last Updated: [Auto] Filter: [Dropdown] │ ├──────────┬──────────┬──────────┬──────────────────┤ │ KPI 1 │ KPI 2 │ KPI 3 │ KPI 4 │ │ $1.2M │ 45% │ 128 │ $47 │ │ ▲ 12% │ ▼ -3% │ ▲ 8% │ ● Flat │ ├──────────┴──────────┴──────────┴──────────────────┤ │ │ │ [Primary Chart — Revenue Trend] │ │ │ ├─────────────────────┬───────────────────────────────┤ │ [Secondary Chart] │ [Table / Top Items] │ │ [Category Split] │ [Ranked List] │ └─────────────────────┴───────────────────────────────┘
KPI Card Formula Pattern
Current value: =SUMIFS(Data!E:E, Data!A:A, ">="&PERIOD_START, Data!A:A, "<="&PERIOD_END) Previous value: =SUMIFS(Data!E:E, Data!A:A, ">="&PREV_START, Data!A:A, "<="&PREV_END) Change %: =(CURRENT - PREVIOUS) / ABS(PREVIOUS) Indicator: =IF(CHANGE>0.05, "▲", IF(CHANGE<-0.05, "▼", "●")) Display: =INDICATOR & " " & TEXT(ABS(CHANGE), "0.0%")
Chart Selection Guide
| Data Pattern | Best Chart | Avoid |
|---|---|---|
| Trend over time | Line chart | Pie chart |
| Part of whole | Stacked bar or donut | 3D pie |
| Comparison | Horizontal bar | Radar chart |
| Distribution | Histogram | Line chart |
| Relationship | Scatter plot | Bar chart |
| KPI vs target | Bullet chart or gauge | Complex chart |
| Geographic | Heat map or filled map | Bar chart |
7 Chart Rules
- Title = Insight, not description. "Revenue grew 23% in Q3" not "Q3 Revenue Chart"
- Start Y-axis at zero for bar charts. Line charts can truncate with clear labeling.
- Max 5-7 data series per chart. Use "Other" category for the rest.
- Remove chartjunk — No 3D effects, gradient fills, excessive gridlines.
- Use consistent colors — Same category = same color across all charts.
- Label directly on chart where possible. Minimize legend lookups.
- Sort meaningfully — By value (largest→smallest) or chronologically. Never alphabetically unless it's the only logical order.
Interactive Dashboard Controls
Filter by dropdown: 1. Config sheet: Data validation dropdown for Region, Period, Category 2. Dashboard formulas use dropdown value: =SUMIFS(Data!E:E, Data!C:C, CONFIG_REGION, Data!A:A, ">="&CONFIG_START) Sparklines (in-cell mini charts): =SPARKLINE(B2:M2, {"charttype","line"; "color","#2563eb"; "linewidth",2})
Phase 7: Data Import & Integration
Import Method Selection
| Source | Method | Refresh |
|---|---|---|
| CSV/Excel file | Manual import / Power Query | Manual |
| Google Sheets (other) | IMPORTRANGE | Auto (varies) |
| Web page table | IMPORTHTML / Power Query | Auto / manual |
| API / JSON | IMPORTDATA / Apps Script / Power Query | Scheduled |
| Database | Power Query / ODBC | Scheduled |
| Another sheet (same workbook) | Direct reference | Real-time |
Google Sheets Import Functions
From another spreadsheet: =IMPORTRANGE("spreadsheet_url", "Sheet1!A1:D100") From web page (table): =IMPORTHTML("url", "table", 1) From CSV: =IMPORTDATA("csv_url") From XML/RSS: =IMPORTXML("url", "//item/title")
Excel Power Query Patterns
1. Data → Get Data → From [Source] 2. Transform in Power Query Editor 3. Close & Load (to table or connection only) Essential transforms: - Remove columns → Right-click header → Remove - Filter rows → Click filter arrow - Split column → Transform → Split Column - Unpivot → Select ID columns → Unpivot Other Columns - Merge queries → Home → Merge (= VLOOKUP but better) - Append queries → Home → Append (= UNION)
IMPORTRANGE Best Practices
Rules: 1. Authorize on first use (one-time popup) 2. Use named ranges in source spreadsheet 3. Wrap in IFERROR for graceful failures 4. Minimize imported range — don't import entire sheets 5. Cache results if auto-refresh causes slowness Pattern: =IFERROR( IMPORTRANGE(SOURCE_URL, "Data!A1:D"&SOURCE_ROW_COUNT), "⚠️ Connection failed — check source spreadsheet access" )
Phase 8: Automation & Scripts
Google Apps Script Essentials
// Auto-populate timestamp on edit function onEdit(e) { const sheet = e.source.getActiveSheet(); if (sheet.getName() === "Data" && e.range.getColumn() >= 2) { sheet.getRange(e.range.getRow(), 1).setValue(new Date()); } } // Email report on schedule (set up trigger) function sendWeeklyReport() { const ss = SpreadsheetApp.getActiveSpreadsheet(); const dashboard = ss.getSheetByName("Dashboard"); const kpi1 = dashboard.getRange("B2").getDisplayValue(); const kpi2 = dashboard.getRange("C2").getDisplayValue(); MailApp.sendEmail({ to: "team@company.com", subject: `Weekly Report — ${Utilities.formatDate(new Date(), "GMT", "MMM dd")}`, htmlBody: `<h2>Weekly KPIs</h2><p>Revenue: ${kpi1}</p><p>Growth: ${kpi2}</p>` }); } // Auto-archive rows older than 90 days function archiveOldRows() { const ss = SpreadsheetApp.getActiveSpreadsheet(); const data = ss.getSheetByName("Data"); const archive = ss.getSheetByName("Archive"); const cutoff = new Date(); cutoff.setDate(cutoff.getDate() - 90); const rows = data.getDataRange().getValues(); for (let i = rows.length - 1; i >= 1; i--) { if (rows[i][0] < cutoff) { archive.appendRow(rows[i]); data.deleteRow(i + 1); } } }
Excel VBA Essentials
' Auto-format new entries Private Sub Worksheet_Change(ByVal Target As Range) If Not Intersect(Target, Range("A:A")) Is Nothing Then Application.EnableEvents = False Target.Offset(0, 5).Value = Now Application.EnableEvents = True End If End Sub ' Refresh all Power Query connections Sub RefreshAllData() ThisWorkbook.RefreshAll MsgBox "All data refreshed at " & Now End Sub
Automation Decision Guide
| Task | Google Sheets | Excel |
|---|---|---|
| On-edit timestamp | Apps Script onEdit | VBA Worksheet_Change |
| Scheduled email | Apps Script + trigger | Power Automate |
| Data refresh | Apps Script + trigger | Power Query + schedule |
| PDF export | Apps Script | VBA + SaveAs |
| Cross-system sync | Apps Script + API | Power Automate / VBA |
| Custom functions | Apps Script CUSTOM_FUNCTION | VBA UDF or LAMBDA |
Phase 9: Performance Optimization
Performance Killers (Ranked)
| Issue | Impact | Fix |
|---|---|---|
| INDIRECT/OFFSET (volatile) | 🔴 Critical | Replace with INDEX/XLOOKUP |
| Whole-column references (A:A) | 🔴 Critical | Use bounded ranges (A2:A1000) |
| ARRAYFORMULA on huge ranges | 🟡 High | Limit range or use QUERY |
| Excessive conditional formatting | 🟡 High | Reduce rules, use bounded ranges |
| Too many IMPORTRANGE | 🟡 High | Consolidate, cache locally |
| Unused sheets with formulas | 🟢 Medium | Delete or clear unused sheets |
| Complex nested IFs | 🟢 Medium | Replace with SWITCH/IFS/XLOOKUP |
| Heavy formatting (images, shapes) | 🟢 Medium | Minimize decorative elements |
Google Sheets Performance Rules
- Keep workbook under 5M cells (ideal: <500K)
- Limit IMPORTRANGE to <10 per workbook
- Use QUERY instead of multiple SUMIFS when possible
- Put ARRAYFORMULA results on a dedicated calc sheet
- Avoid NOW()/TODAY() in frequently-recalculated areas
Excel Performance Rules
- Use tables (Ctrl+T) for structured data — better performance than raw ranges
- Power Query > formulas for data transformation
- XLOOKUP > VLOOKUP > INDEX/MATCH for speed
- Turn off auto-calculation during bulk edits:
Application.Calculation = xlManual - Use Power Pivot for >100K rows instead of formulas
Phase 10: Collaboration & Governance
Access Control Strategy
| Role | Permissions | Implementation |
|---|---|---|
| Owner | Full control | Original creator |
| Editor | Edit data, not structure | Share with edit, protect structure sheets |
| Analyst | Edit inputs, view outputs | Protect all except input cells |
| Viewer | View only | Share as viewer |
| Commenter | View + comment | Share as commenter |
Sheet Protection Pattern
1. Protect entire workbook structure (prevent sheet add/delete/rename) 2. Protect each sheet 3. UNLOCK only input cells (blue-coded) 4. Set password for admin overrides 5. Document which cells are editable in README
Version Control
Naming: YYYY-MM-DD_ModelName_vX.Y X = major change (new section, restructure) Y = minor change (formula fix, data update) Changelog (on README sheet): | Date | Version | Author | Change | |------|---------|--------|--------| | 2025-03-15 | 2.1 | Jane | Added Q2 actuals | | 2025-03-01 | 2.0 | John | Restructured revenue model |
Collaboration Rules
- Never edit someone else's model without telling them
- Use named versions before major changes (Google Sheets: File → Version history → Name current version)
- Comment on cells — don't explain in chat, explain in the sheet
- One editor at a time for complex formula areas — use "editing" flag cell
- Weekly review — Check for broken references, stale data, unused sheets
Phase 11: Common Templates
Budget Tracker Template
Columns: Month | Category | Subcategory | Budgeted | Actual | Variance | % Variance KPIs: Total Budget | Total Spent | Remaining | Burn Rate | Projected Year-End Charts: Budget vs Actual (bar), Spend by Category (donut), Monthly Trend (line) Formulas: Variance: =Actual - Budgeted % Variance: =IF(Budgeted=0, "", (Actual-Budgeted)/ABS(Budgeted)) Burn Rate: =SUMIFS(Actual, Month, "<="&TODAY()) / (MONTH(TODAY()) * Total_Budget / 12)
Project Tracker Template
Columns: Task | Owner | Status | Priority | Start | Due | Days Left | % Complete | Notes Status: 🔴 Blocked | 🟡 In Progress | 🟢 Complete | ⚪ Not Started Formulas: Days Left: =IF(Status="🟢 Complete", "✅", MAX(0, Due-TODAY())) Overdue flag: =IF(AND(Status<>"🟢 Complete", Due<TODAY()), "⚠️ OVERDUE", "") Completion %: =COUNTIF(Status, "🟢 Complete") / COUNTA(Status) Dashboard: Gantt-style with conditional formatting date bars
Sales Pipeline Template
Columns: Deal | Company | Stage | Amount | Probability | Weighted | Owner | Close Date | Days in Stage | Next Action Stages: Prospect (10%) | Qualified (25%) | Proposal (50%) | Negotiation (75%) | Closed Won (100%) | Lost (0%) Formulas: Weighted: =Amount * Probability Pipeline: =SUMIFS(Weighted, Stage, "<>"&"Lost", Stage, "<>"&"Closed Won") Velocity: =AVERAGE(Days_to_Close_for_Won_Deals) Dashboard: Pipeline by stage (funnel), Forecast vs quota, Win rate trend
OKR Tracker Template
Columns: Objective | Key Result | Metric | Start | Current | Target | Score | Status Score: =MIN(1, (Current - Start) / (Target - Start)) Status: =IF(Score>=0.7, "🟢", IF(Score>=0.4, "🟡", "🔴")) Overall: =AVERAGE(Score) across all KRs per Objective
Phase 12: Quality & Maintenance
Spreadsheet Quality Rubric (0-100)
| Dimension | Weight | Scoring |
|---|---|---|
| Architecture | 15% | Clear sheet structure, data flow direction, README |
| Formula Quality | 20% | Named ranges, error handling, no hardcoding |
| Data Validation | 15% | Input constraints, dropdowns, type checking |
| Visual Design | 10% | Consistent formatting, color coding, readability |
| Documentation | 15% | Cell notes, README, changelog, instructions |
| Performance | 10% | No volatile functions, bounded ranges, fast recalc |
| Error Handling | 10% | IFERROR wrappers, validation checks, no broken refs |
| Maintainability | 5% | Protected structure, clear ownership, versioned |
Monthly Maintenance Checklist
- Check for #REF! and #N/A errors across all sheets
- Verify data source connections are refreshing
- Review and update assumptions (Config sheet)
- Remove unused sheets and named ranges
- Check file size — if growing, archive old data
- Test all dropdowns and validation rules
- Update README with any changes made
- Create named version snapshot
10 Spreadsheet Killers
| Mistake | Impact | Fix |
|---|---|---|
| Hardcoded numbers in formulas | Can't audit or update | Named ranges + Config sheet |
| No error handling | #N/A cascades break everything | IFERROR on all lookups |
| Whole-column references | Slow, crashes on large data | Bounded ranges |
| Circular references | Unpredictable results | Redesign calculation flow |
| No documentation | "What does this formula do?" | README + cell notes |
| No data validation | Garbage in = garbage out | Dropdowns + constraints |
| One mega-sheet | Unmaintainable, slow | Split by function |
| No backup/versions | One mistake = lost work | Named versions + exports |
| Copy-paste instead of formulas | Stale data, inconsistencies | Use references/IMPORTRANGE |
| Manual processes that should be automated | Error-prone, time-wasting | Scripts or scheduled refreshes |
Edge Cases
Migrating Excel ↔ Google Sheets
- XLOOKUP works in both (Excel 365 + Google Sheets)
- QUERY is Google Sheets only — replace with Power Query in Excel
- ARRAYFORMULA is Google Sheets — Excel uses Ctrl+Shift+Enter or dynamic arrays
- Apps Script → no Excel equivalent. Use VBA or Power Automate.
- Power Query / Power Pivot → no Google Sheets equivalent. Use QUERY or BigQuery connector.
- Test all formulas after migration. Named ranges may break.
Multi-Currency Spreadsheets
=Amount * XLOOKUP(Currency, FX_Rates!A:A, FX_Rates!B:B) Or with GOOGLEFINANCE: =Amount * GOOGLEFINANCE("CURRENCY:GBPUSD")
Large Dataset Workarounds (>100K rows)
- Split data across multiple sheets by time period
- Use pivot tables / QUERY instead of row-level formulas
- Import summarized data, not raw transactions
- Consider BigQuery + Connected Sheets (Google) or Power Pivot (Excel)
- If you need >500K rows, graduate to a database
Natural Language Commands
When working with spreadsheets, you can ask:
- "Audit this spreadsheet for quality issues"
- "Design a financial model for [business type]"
- "Create a dashboard layout for [metrics]"
- "Write the formulas for [calculation]"
- "Optimize this spreadsheet for performance"
- "Build a data validation system for [input type]"
- "Create an Apps Script to [automate task]"
- "Design a template for [use case]"
- "Review this formula and suggest improvements"
- "Help me migrate this from Excel to Google Sheets"
- "Set up a scenario analysis for [model]"
- "Build a KPI tracker for [department]"
⚡ Level Up — AfrexAI Context Packs
This skill covers spreadsheet engineering methodology. For industry-specific financial models, dashboards, and templates:
- 💰 SaaS Context Pack — MRR/ARR models, SaaS metrics dashboards, cohort analysis templates
- 🏦 Fintech Context Pack — Financial modeling, risk calculators, compliance trackers
- 🏭 Manufacturing Context Pack — Production trackers, inventory models, cost analysis
- 🏗️ Construction Context Pack — Project budgets, bid calculators, resource planning
$47 per pack — Complete AI agent context for your industry.
Browse all packs: AfrexAI Storefront →
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Built by AfrexAI — AI agents that compound capital and code.