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Templates

Create custom naming templates using natural language to extract information from your files

What are Templates?

Templates let you tell NameQuick exactly how to name your files. Write instructions in plain English, and the AI will extract the information you need.

You write a template like this:

{date}_{company name}_{invoice total}

NameQuick creates filenames like this:

2024-03-15_Apple_$299.99.pdf

Which Files Can I Use Templates With?

Documents & Images

Works with all AI providers

`PDF`, `PNG`, `JPG`, `JPEG`, `WEBP`

Text Files

OpenAI & Google Gemini

`TXT`, `MD`, `CSV`, `DOCX`

Real-World Examples

See how different professionals use templates to organize their files automatically

Invoice Processing

For accounting departments

Your template instructions:

1

{date}

2

{company name}

3

{invoice number}

4

{total amount}

Before & After:

Before

scan_001.pdf

After

2024-03-15_Amazon_INV-4711_$156.99.pdf

Research Papers

For academics & students

Your template instructions:

1

{publication year}

2

{first author}

3

{paper title}

Before & After:

Before

download.pdf

After

2024_Smith_Neural_Networks.pdf

Political Image Analysis

For journalists & researchers

Your template instructions:

1

{politician name}

2

{sentiment}

3

{scenario}

Before & After:

Before

IMG_2024.jpg

After

Biden_Positive_Speech.jpg

How to Write Templates

Writing Natural Language Instructions

Your instructions tell the AI what to look for. Be specific and descriptive:

Good Instructions

  • • "company name"
  • • "invoice number"
  • • "total amount"

Vague Instructions

  • • "date"
  • • "name"
  • • "amount"

Complete Template Example:

{date}_{company name}_{invoice number}

Produces: 2024-03-15_Apple_INV-2024-001.pdf

Transformations

Clean up and standardize extracted data with transformation rules

What are Transformations?

Transformations modify the data after AI extraction but before creating the filename. Write rules in plain English to format your data consistently.

Step 1: Original Template:

{date}_{vendor}_{type}_{amount}

Step 2: AI Extracts:

date: "March 15, 2024" • vendor: "Apple Inc." • type: "Invoice" • amount: "$299.99"

Step 3: You Apply Transformations:

"Convert vendor to lowercase"

"Replace all spaces with underscores"

"Format date as YYYY-MM-DD"

Step 4: Final Result:

2024-03-15_apple_inc_invoice_$299.99.pdf

Transformation Scope

Choose where your transformations apply for maximum control and reliability

All Fields
Global Application

Applies the transformation to every field in your template

Example:

"Convert to lowercase"

Result:

All company names, dates, amounts become lowercase

Exact Field
Targeted Application
Recommended

Applies the transformation only to specific fields you choose

Example:

"Convert to lowercase" → company field only

Result:

Only company names become lowercase, dates stay formatted

✓ More reliable: Won't break dates, numbers, or currencies

Pro Tip: Use Exact Fields for Better Results

Exact field transformations are more reliable because they target specific data types. For example, applying "lowercase" to a company field keeps your dates and amounts properly formatted, while "All Fields" might accidentally convert "March 15, 2024" to "march 15, 2024".

Common Transformation Examples

Text Transformations

"Convert to lowercase"

Apple Inc. → apple inc.

"Replace spaces with underscores"

New York → New_York

"Remove special characters"

Invoice #123! → Invoice 123

"Get first word only"

Apple Computer Inc. → Apple

Custom Transformations

Write any transformation in plain English:

"Keep only numbers" → invoice_number field

Invoice #2024-001 → 2024001

"Convert to lowercase" → vendor field

Apple Inc. → apple inc.

"Format as phone number" → contact field

4155551234 → (415) 555-1234

"Remove after @ symbol" → email field

john@company.com → john

Tips & Best Practices

Writing Better Instructions

Be Specific

"Find invoice date in top right corner" beats "find date"

Provide Alternatives

"Look for 'Total' or 'Amount Due' or 'Balance'"

Use Visual Cues

"Near the logo", "In bold text", "Largest number"

Test Thoroughly

Use files from different sources before saving

Common Pitfalls to Avoid

Too Vague

Avoid: "number", "text", "value"

Over-Complex

Don't write essays - keep instructions focused

No Fallbacks

Always provide alternative search terms

Wrong Scope

Don't apply "lowercase" to dates or numbers

Work Iteratively

If extraction or transformation doesn't work perfectly, adapt your instructions based on what the AI actually sees.

Example: Euro Symbol Recognition

Sometimes AI recognizes € as "e". Instead of "Convert Euro to EUR", use:

"Convert Euro sign and e to EUR"