GPT for Sheets - AI Sheet Agent Guide

GPT for Sheets: What It Does

GPT for Sheets helps you work with the current active sheet using plain English.

The most useful pattern is simple:

• Read one or more existing columns
• Generate a new column with cleaned, extracted, classified, translated, summarized, or standardized output
• Or, if the sheet is empty, generate a full table

In one sentence:

GPT for Sheets is best at "read the current sheet, generate a new result column, preview it, then apply it."

How the Plugin Works

Every task follows a preview-first workflow:

1. Open your Google Sheet
2. Launch Extensions -> Funshow -> GPT for Sheets
3. Describe what you want in plain English
4. The add-on sends the current sheet structure to the backend
5. You get a preview plan with sample before/after rows
6. Review the proposed change
7. Click confirm to execute

For most tasks, GPT for Sheets writes to a new column instead of changing your original data.

If the sheet is empty, it can generate a full table instead.

Best Way to Write a Request

The clearest requests usually include:

• the source column name
• what transformation you want
• where the result should go

Good examples:

• "Remove Inc., LLC, Ltd, and Corp. from the Company column and write the cleaned names to a new column."
• "Extract the domain from the Website column into a new column."
• "Translate the Product Title column from English to German into a new column."
• "Create a profit margin column using Profit divided by Revenue."

Less effective examples:

• "Fix this sheet"
• "Clean the data"
• "Make it better"

What GPT for Sheets Can Do Well

These are the most common and most reliable operations in the current version:

1. Clean one text column and write results to a new column
2. Extract fields into a new column
3. Classify rows into labels
4. Translate text into a new column
5. Summarize long text into a new column
6. Rewrite or standardize text into a new column
7. Detect sentiment or intent into a new column
8. Generate a formula column
9. Sort the current sheet
10. Generate a full table on an empty sheet

What It Cannot Do in This MVP

The current agent is intentionally narrow.

It does not handle:

• cross-sheet workflows
• multi-step automations across multiple tabs
• delete row / delete column / destructive cleanup operations
• overwrite-in-place editing of existing columns
• external web research
• exact partial-range transformations with complex targeting rules

If you need those, use a manual workflow or split the job into smaller single-sheet steps.

Quick Capability Summary

Area	Supported now	Notes
Current active sheet	Yes	Only the open sheet is used
Write to new column	Yes	Default behavior
Full table generation on empty sheet	Yes	For list/table generation tasks
Formula columns	Yes	Deterministic formulas only
Sort current sheet	Yes	Sorts current sheet data range
Preview before execute	Yes	Required workflow
Cross-sheet actions	No	Not in MVP
Delete or overwrite existing columns	No	Not supported
External data lookup	No	Not a research agent
Complex workflows	Limited	Best with one-step tasks

10 Useful Examples

Below are the 10 most useful kinds of requests for the current agent, with examples of what changes in the sheet.

1. Clean a Text Column Into a New Column

Use this when you want to remove suffixes, trim spaces, normalize case, or clean messy values.

Example request

Remove legal suffixes such as Inc., LLC, Ltd, and Corp. from the Company column and write the cleaned company names to a new column.

Before: Company	After: Standardized Company
Acme Inc.	Acme
Globex LLC	Globex
Initech Ltd	Initech

Good use cases:

• remove company suffixes
• normalize title casing
• trim extra spaces
• standardize punctuation

2. Extract a Field Into a New Column

Use this when one column contains useful structured data hidden inside text.

Example request

Extract the domain from the Website column into a new column.

Before: Website	After: Domain
https://www.acme.com/about	acme.com
http://globex.co.uk	globex.co.uk
initech.io	initech.io

Other extraction examples:

• country from address
• first name from full name
• last name from full name
• job level from job title

3. Classify Rows Into Labels

Use this when you want lightweight AI categorization.

Example request

Categorize each lead as Enterprise, SMB, or Startup based on Company and Notes, then write the result to a new column.

Company	Notes	After: Segment
Stripe	Global payments platform	Enterprise
Tiny Bakery	Local bakery with 5 staff	SMB
SeedRocket	Early-stage SaaS startup	Startup

This works well for:

• lead quality
• product category
• priority labels
• support ticket type

4. Translate a Column Into a New Column

Use this when you want a side-by-side translated version while keeping the original text.

Example request

Translate the Title column from English to Chinese into a new column.

Before: Title	After: Title (Chinese)
Wireless Noise Cancelling Headphones	无线降噪耳机
Portable Monitor for Laptop	便携式笔记本显示器

This is useful for:

• product titles
• descriptions
• ad copy
• support responses

5. Summarize Long Text Into a New Column

Use this when one column is too long to scan quickly.

Example request

Summarize the Notes column into one short sentence in a new column.

Before: Notes	After: Notes Summary
Customer asked about annual pricing, requested SSO support, and wants a security review next week.	Interested in annual plan and enterprise security features.
Prospect said the product is too expensive and wants a smaller starter package.	Price-sensitive lead asking for a lower-tier plan.

This is especially useful for:

• CRM notes
• meeting notes
• support tickets
• user feedback

6. Rewrite or Standardize Text Into a New Column

Use this when the source text is inconsistent and you want one unified style.

Example request

Rewrite the Job Title column into a standardized short format in a new column.

Before: Job Title	After: Standardized Job Title
Sr. Software Eng.	Senior Software Engineer
VP Sales - APAC	Vice President of Sales
founder & ceo	Founder and CEO

Other examples:

• standardize product titles
• normalize department names
• unify status wording
• rewrite descriptions in a consistent tone

7. Detect Sentiment or Intent Into a New Column

Use this when you want each row tagged with a simple AI judgment.

Example request

Classify each customer email as Inquiry, Complaint, or Follow-up in a new column.

Before: Email	After: Intent
Can you send pricing for 50 users?	Inquiry
The export keeps failing and we need a fix today.	Complaint
Checking back on my demo request from last week.	Follow-up

You can also use this for:

• positive / neutral / negative sentiment
• urgent / non-urgent tickets
• interested / not interested leads

8. Generate a Formula Column

Use this when the result should be deterministic and based on existing numeric or date columns.

Example request

Create a profit margin column using Profit divided by Revenue, and format it as a percentage.

Revenue	Profit	After: Profit Margin
10000	2500	25.00%
25000	5000	20.00%

Other good formula tasks:

• conversion rate
• gross margin
• days between two dates
• weighted score
• pass/fail logic

9. Sort the Current Sheet

Use this when you want the current sheet reordered by one column.

Example request

Sort the current sheet by Revenue from highest to lowest.

Before order	Revenue
Deal A	1000
Deal B	8000
Deal C	3500

After order	Revenue
Deal B	8000
Deal C	3500
Deal A	1000

This is best for:

• highest value first
• newest date first
• priority-based ranking

10. Generate a Full Table on an Empty Sheet

Use this when the sheet is empty and you want GPT for Sheets to create a structured table from scratch.

Example request

Generate a table of the top 5 AI companies with columns Rank, Company, Website, and Primary Use Case.

Rank	Company	Website	Primary Use Case
1	OpenAI	openai.com	General-purpose AI models and assistants
2	Anthropic	anthropic.com	AI assistants and model safety
3	Google DeepMind	deepmind.google	Research and multimodal AI systems

This works well for:

• top websites lists
• glossary tables
• keyword lists
• country / capital study sheets
• starter research tables you will refine manually later

Before You Click Confirm

Always check:

• Is the source column correct?
• Is the new column name sensible?
• Do the sample rows look right?
• Is the operation writing to a new column instead of changing original data?

If the preview looks wrong, rewrite the request more clearly before running it.

Prompt Templates You Can Reuse

Try these patterns:

• Clean the [Column Name] column and write the result to a new column.
• Extract [field] from [Column Name] into a new column.
• Classify each row as [Label A], [Label B], or [Label C] based on [Column 1] and [Column 2].
• Translate the [Column Name] column from [Language A] to [Language B] into a new column.
• Summarize the [Column Name] column into one short sentence in a new column.
• Standardize the [Column Name] column into a consistent format in a new column.
• Create a [New Column Name] formula column using [Column A] and [Column B].
• Sort the current sheet by [Column Name] in descending order.
• Generate a table with columns [A], [B], and [C] on this empty sheet.

Tips for Better Results

• Use exact column names when possible
• Ask for one clear operation at a time
• Prefer "write to a new column" phrasing
• If classification is subjective, name the labels explicitly
• If you want formula output, say so clearly
• If the sheet is empty, specify the columns you want in the generated table

When GPT for Sheets Is the Right Tool

Use GPT for Sheets when you want:

• a fast cleanup pass
• a repeatable enrichment column
• a readable preview before changing data
• AI help without manual formulas for every row

Avoid it when you need:

• workflow automation across multiple sheets
• exact scripting logic
• external enrichment from the web
• destructive cleanup

Related Articles

• Quick Start Guide
• Translate Google Sheets
• Troubleshooting

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Need help with GPT for Sheets? Contact us at [email protected].