Excel formula builder with step-by-step explanation

Turns a described spreadsheet calculation into a working Excel formula plus a plain-language walkthrough of every function, operator and reference it uses.

PLPromptByte Library@promptbytePublished Aug 25

TextData & Analysis #data analysis #excel #formulas #spreadsheets

Version 1 of 1 · published Aug 25, 2026Version 1 · only version

Example output

See all results

Anthropic · Claude Sonnet 5 PLPromptByte Library Version 1

Prompt

Version 1 · 3 variables · 2 required

Fill in the values below — the customized prompt updates as you type. marks a required value.

Calculation you want{{desired_calculation}}

What the formula should work out, in plain language. e.g. "total revenue per sales rep for Q4 2025 shipped orders only".

Input data / cell references{{input_data}}

Sheet names, column letters and row ranges the formula will read, plus where the result goes.

Conditions and constraints(optional){{constraints}}

Excel version, error handling, performance limits, anything the formula must or must not do. Default: must be robust to blank cells and return 0 instead of an error

Fill in Calculation you want, Input data / cell references to copy the customized prompt.

Resultsfor version 1

All models Claude Sonnet 51

Version 1 · only version

Claude Sonnet 5 result by PromptByte Library
Anthropic · Claude Sonnet 5 PLPromptByte Library (@promptbyte)Version 1Published Aug 25
Compare
**Recommended formula** — enter in Summary!B2 and fill down: =IFERROR(SUMIFS(Orders!$D$2:$D$5000, Orders!$B$2:$B$5000, $A2, Orders!$C$2:$C$5000, "Shipped", Orders!$A$2:$A$5000, ">="&DATE(2025,10,1), Orders!$A$2:$A$5000, "<="&DATE(2025,12,31)), 0) **How it works, step by step** 1. SUMIFS(sum_range, criteria_range1, criteria1, ...) adds values from Orders!D2:D5000 only for rows where every criteria pair matches. Unlike SUMIF it takes multiple conditions, so no helper column is needed. 2. Orders!$B$2:$B$5000 = $A2 matches the rep name in column A of the Summary sheet. The $ locks the column…
Community submittedFull output
Settings: Unknown
Open result

Showing all 1 public result from Claude Sonnet 5 on version 1.

Usage notes

Best results come from being specific in input_data: name the sheet, the exact column letters and the row range, rather than saying "my sales table". Put hard requirements in constraints — supported Excel version, error handling, whether the formula must fill down a column.

The same prompt works for Google Sheets if you say so in constraints; ask for the ARRAYFORMULA or QUERY variant there.

Always spot-check the returned formula against a few rows you can verify by hand before applying it to a whole workbook. Models are good at formula shape and weak at the exact boundaries of your data (off-by-one row ranges, mixed date formats, text-formatted numbers).

Attribution: adapted from https://github.com/f/prompts.chat by f (Fatih Kadir Akın), licensed CC0-1.0. Source file: https://github.com/f/prompts.chat/blob/main/PROMPTS.md

Models represented

1 public result from 1 model

code · sql
```
**Assumptions**

- `order_items.order_id` joins to `orders.id`, and `products.category_id` joins to `categories.id`. These are inferred from the naming convention, since no foreign keys were listed.
- "Last 90 days" is measured against `orders.order_date` relative to today, inclusive of today.
- Revenue is `quantity * unit_price` summed over line items; there is no discount or tax column in the schema, so none is applied.
- Cancelled orders are excluded. If `status` uses different values than `'
```
Code preview: **Assumptions** - `order_items.order_id` joins to `orders.id`, and `products.category_id` joins to `categories.id`. These are inferred from the naming convention, since no foreign keys were listed. - "Last 90 days" is measured against `orders.order_date` relative to today, inclusive of today. - Revenue is `quantity * unit_price` summed over line items; there is no discount or tax column in the schema, so none is applied. - Cancelled orders are excluded. If `status` uses different values than `'
SQL query generator from a plain-English request
Converts a natural-language data requirement plus a table schema into a syntactically correct SQL query for a named database, with its assumptions stated up front.
CodeData & Analysis OpenAI · GPT-5.5
PL@promptbyteAug 27
Score 1
0 comments1 results
No public results yet
Categorize an expense list with an auditable review queue
Apply your own expense categories consistently, preserve original transactions and flag ambiguous items, duplicates and possible recurring charges.
TextProductivity
PL@promptbyteSep 8
Score 0
0 comments0 results
No public results yet
Audit SQL joins for duplicate rows and inflated totals
Check join cardinality and aggregation grain to explain duplicate rows or double-counted measures before changing a reporting query.
TextData & Analysis
PL@promptbyteSep 8
Score 0
0 comments0 results
No public results yet
Design a forecast backtest that respects time and information
Specify temporal evaluation, leakage checks, baselines and business-relevant metrics before judging a forecasting model.
TextData & Analysis
PL@promptbyteSep 8
Score 0
0 comments0 results
No public results yet
Critique an existing chart for misleading interpretation
Review a chart's scales, labels, aggregation and claims, separating visual issues from data questions that need verification.
TextData & Analysis
PL@promptbyteSep 8
Score 0
0 comments0 results
No public results yet
Classify comment sentiment with traceable evidence
Label supplied comments consistently while preserving mixed opinions, unclear cases and the exact words supporting each label.
TextData & Analysis
PL@promptbyteSep 8
Score 0
0 comments0 results

Browse Data & Analysis

Excel formula builder with step-by-step explanation

Example output

Prompt

Resultsfor version 1

Something wrong with this prompt?

SQL query generator from a plain-English request

Categorize an expense list with an auditable review queue

Audit SQL joins for duplicate rows and inflated totals

Design a forecast backtest that respects time and information

Critique an existing chart for misleading interpretation

Classify comment sentiment with traceable evidence

Discussion 0

Example output

Prompt

Resultsfor version 1

Something wrong with this prompt?

Related prompts

SQL query generator from a plain-English request

Categorize an expense list with an auditable review queue

Audit SQL joins for duplicate rows and inflated totals

Design a forecast backtest that respects time and information

Critique an existing chart for misleading interpretation

Classify comment sentiment with traceable evidence

Discussion 0