Skill: 1kalin/afrexai-spreadsheet-engineering (version 1.0.0)

# 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 ```yaml 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 1. **One direction of flow** — Data flows left→right or top→bottom. Never circular. 2. **Inputs separate from calculations** — NEVER hardcode numbers in formulas. Use named ranges. 3. **One fact in one place** — If a value is used in 3 places, define it once and reference it. 4. **Color code by purpose** — Blue = input, Black = formula, Green = linked from other sheet, Red = warning. 5. **Freeze panes on every data sheet** — Header row and label columns always visible. 6. **Protect formula cells** — Lock everything except input cells. Prevent accidental overwrites. 7. **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 | `=SUM(B2:B100)` | | L2 Intermediate | VLOOKUP/XLOOKUP, SUMIFS, INDEX/MATCH, TEXT | `=XLOOKUP(A2,Ref!A:A,Ref!B:B)` | | L3 Advanced | ARRAYFORMULA, QUERY, INDIRECT, nested IFs | `=QUERY(Data!A:F,"SELECT A,SUM(F) GROUP BY A")` | | L4 Expert | LAMBDA, MAP/REDUCE, LET, dynamic arrays, MAKEARRAY | `=LET(data,A2:A100,filtered,FILTER(data,data>0),SORT(filtered))` | ### 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 1. **NEVER hardcode values** — Use named ranges or a Config sheet 2. **Wrap external lookups in IFERROR** — `=IFERROR(XLOOKUP(...), "Not Found")` 3. **Use LET for formulas >100 chars** — Readable, debuggable, faster 4. **Prefer XLOOKUP over VLOOKUP** — More flexible, no column counting 5. **One formula per cell** — Don't nest 5+ functions. Break into helper columns. 6. **Comment complex formulas** — Use cell notes or a documentation column 7. **Test with edge cases** — Empty cells, zeros, dates before 1900, text in number fields 8. **Avoid INDIRECT for performance** — It's volatile (recalculates every time) 9. **Use structured references in tables** — `=SUM(Table1[Amount])` not `=SUM(D:D)` 10. **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 | | Email | Contains @ | Custom: `=ISNUMBER(FIND("@",A2))` | | Phone | Length check | Custom: `=AND(LEN(A2)>=10, LEN(A2)<=15)` | | Required field | Not blank | Custom: `=LEN(TRIM(A2))>0` | | ID/Code | Unique + format | Custom: `=AND(COUNTIF(A:A,A2)=1, LEN(A2)=8)` | ### 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) 1. 🔴 **Errors** — Any cell with #REF!, #N/A, #VALUE! → Red background 2. 🟡 **Warnings** — Values outside expected range → Yellow background 3. 🟢 **Positive** — On-target metrics → Green text 4. 📊 **Data bars** — Numeric ranges → Proportional bars 5. 🎯 **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 ```yaml 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 1. **Title = Insight**, not description. "Revenue grew 23% in Q3" not "Q3 Revenue Chart" 2. **Start Y-axis at zero** for bar charts. Line charts can truncate with clear labeling. 3. **Max 5-7 data series** per chart. Use "Other" category for the rest. 4. **Remove chartjunk** — No 3D effects, gradient fills, excessive gridlines. 5. **Use consistent colors** — Same category = same color across all charts. 6. **Label directly** on chart where possible. Minimize legend lookups. 7. **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 ```javascript // 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: "[REDACTED_SECRET]", 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 ```vba ' 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 1. Keep workbook under 5M cells (ideal: <500K) 2. Limit IMPORTRANGE to <10 per workbook 3. Use QUERY instead of multiple SUMIFS when possible 4. Put ARRAYFORMULA results on a dedicated calc sheet 5. Avoid NOW()/TODAY() in frequently-recalculated areas ### Excel Performance Rules 1. Use tables (Ctrl+T) for structured data — better performance than raw ranges 2. Power Query > formulas for data transformation 3. XLOOKUP > VLOOKUP > INDEX/MATCH for speed 4. Turn off auto-calculation during bulk edits: `Application.Calculation = xlManual` 5. 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 1. **Never edit someone else's model without telling them** 2. **Use named versions** before major changes (Google Sheets: File → Version history → Name current version) 3. **Comment on cells** — don't explain in chat, explain in the sheet 4. **One editor at a time** for complex formula areas — use "editing" flag cell 5. **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) 1. Split data across multiple sheets by time period 2. Use pivot tables / QUERY instead of row-level formulas 3. Import summarized data, not raw transactions 4. Consider BigQuery + Connected Sheets (Google) or Power Pivot (Excel) 5. 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**](https://afrexai-cto.github.io/context-packs/) — MRR/ARR models, SaaS metrics dashboards, cohort analysis templates - 🏦 [**Fintech Context Pack**](https://afrexai-cto.github.io/context-packs/) — Financial modeling, risk calculators, compliance trackers - 🏭 [**Manufacturing Context Pack**](https://afrexai-cto.github.io/context-packs/) — Production trackers, inventory models, cost analysis - 🏗️ [**Construction Context Pack**](https://afrexai-cto.github.io/context-packs/) — Project budgets, bid calculators, resource planning **$47 per pack** — Complete AI agent context for your industry. Browse all packs: [**AfrexAI Storefront →**](https://afrexai-cto.github.io/context-packs/) --- ## 🔗 More Free Skills by AfrexAI - [afrexai-data-storytelling](https://clawhub.com/afrexai-cto/afrexai-data-storytelling) — Data visualization & dashboard design methodology - [afrexai-personal-finance](https://clawhub.com/afrexai-cto/afrexai-personal-finance) — Complete personal finance operating system - [afrexai-product-analytics](https://clawhub.com/afrexai-cto/afrexai-product-analytics) — Product metrics & analytics engineering - [afrexai-fpa-engine](https://clawhub.com/afrexai-cto/afrexai-fpa-engine) — Financial planning & analysis - [afrexai-automation-strategy](https://clawhub.com/afrexai-cto/afrexai-automation-strategy) — Workflow automation methodology --- *Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI agents that compound capital and code.*

path: README.md
content: # afrexai-spreadsheet-engineering

> Build bulletproof spreadsheets: financial models, dashboards, data systems, and automation. Platform-agnostic methodology for Google Sheets, Excel, and LibreOffice.

## Install

```bash
clawhub install afrexai-spreadsheet-engineering
```

## What's Inside

- **29KB** single SKILL.md — complete spreadsheet engineering methodology
- 12-phase system covering architecture → formulas → dashboards → automation
- Formula patterns library (L1-L4 complexity) with XLOOKUP, QUERY, LAMBDA, LET
- Financial modeling architecture with SaaS revenue models and scenario analysis
- Dashboard design system with KPI cards, chart selection guide, and interactive controls
- Google Apps Script and Excel VBA automation patterns
- Data validation and quality pipeline
- Performance optimization guide (volatile function elimination, bounded ranges)
- 4 ready-to-use templates (budget, project, pipeline, OKR)
- 100-point quality rubric across 8 weighted dimensions
- Platform-agnostic: works for Google Sheets, Excel 365, and LibreOffice

## Quick Start

Ask your agent:
- "Design a financial model for my SaaS business"
- "Audit this spreadsheet for quality issues"
- "Build a dashboard for tracking monthly KPIs"
- "Write a QUERY formula to aggregate sales by region"

## ⚡ Level Up

For industry-specific financial models and templates, check out our **AI Agent Context Packs** ($47 each):

👉 [**Browse All Packs →**](https://afrexai-cto.github.io/context-packs/)

## 🔗 More Free Skills by AfrexAI

- [afrexai-data-storytelling](https://clawhub.com/afrexai-cto/afrexai-data-storytelling) — Data visualization methodology
- [afrexai-personal-finance](https://clawhub.com/afrexai-cto/afrexai-personal-finance) — Personal finance operating system
- [afrexai-automation-strategy](https://clawhub.com/afrexai-cto/afrexai-automation-strategy) — Workflow automation
- [afrexai-fpa-engine](https://clawhub.com/afrexai-cto/afrexai-fpa-engine) — Financial planning & analysis
- [afrexai-prompt-engineering](https://clawhub.com/afrexai-cto/afrexai-prompt-engineering) — Prompt engineering mastery


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)