Presets

Presets are reusable naming patterns: define one once and NameQuick applies it to every similar file.

There are two kinds, and both produce structured, consistent names:

• Templates: build the pattern visually from fields like "Invoice Date" or "Vendor Name". Precise and predictable.
• Custom Prompts: describe the naming in plain language, like "name this with the date and topic". Flexible when you'd rather describe than build.

Need a quick one-off? Smart Rename names files with zero setup. Rename Modes decide whether names apply instantly or wait for your review.

Templates#

Templates give you precise, visual control over the naming. You define what to extract, and NameQuick builds filenames that always follow your pattern.

Extraction Fields#

Fields are the heart of templates. You write them in plain English, and the AI uses your field names as extraction instructions.

Good field names are specific:

Give hints when helpful:

• "Invoice number (usually starts with INV-)"
• "Date the document was signed"
• "Total including tax, formatted as currency"

The more specific your field names, the better the extraction. The AI reads them as instructions for what to find.

The Pattern Builder#

Templates use a visual pattern builder with drag-and-drop pills. Drag to reorder the parts, and click a separator to change it.

Three pill types:

Custom Prompts#

Custom Prompts let you describe the naming in plain language. Instead of building a pattern from fields, you write natural-language instructions and the AI extracts the same structured values. They work well when you would rather describe the result than assemble it field by field.

Creating a Custom Prompt:

1. Open the sidebar and go to Presets
2. Click New and choose Custom Prompt
3. Write natural-language instructions
4. Preview on sample files, then save

Prompts can be as short or detailed as you need. A single prompt can define different patterns per document type, formatting rules, and edge-case handling. The AI reads the full prompt and applies the matching rules to each file.

A more detailed example. This invoice prompt sets a naming pattern, per-document-type rules, and edge cases:

For filename values that are not printed on the document, like ISO week codes or customer codes, see Teach the AI your naming convention.

Text Cleanup#

Text cleanups modify extracted values after AI extraction but before the filename is assembled. You write them in natural language.

Field-specific cleanups apply to individual values (e.g. "Format invoice date as YYYY-MM-DD"). Global cleanups apply to the assembled filename (e.g. "Replace all spaces with hyphens"). Field cleanups run first, then the pattern assembles, then global cleanups run on the result.

Testing and Iterating#

Before applying a template to real files, test it:

1. Open your template in the editor
2. Drop a sample file into the test area
3. AI extraction runs in preview mode (no renames consumed)
4. See the result: Original filename → Generated filename

Use the test area to check whether your preset produces the filenames you expect. If a field extracts the wrong value or the format is off, adjust field names to be more specific, add text cleanups for formatting, or try different sample files. Iterate until the output matches what you need.

Reference#

System Placeholders#

System placeholders insert metadata that does not need AI extraction:

Date formatting:

Customize date format with a colon:

{date:yyyy-MM-dd}      → 2024-03-15
{date:MM-dd-yyyy}      → 03-15-2024
{date:yyyyMMdd}        → 20240315
{datetime:yyyy-MM-dd_HH-mm}  → 2024-03-15_14-30

Separators#

Each gap between pills can have its own separator (underscore _, hyphen -, period ., space, double underscore __, double hyphen --, no separator, or a custom string). You can also customize how multi-word values appear within each field by clicking the separator indicator on a teal user field pill.

Example: If AI extracts "Acme Corporation":

Advanced Features#

Field Conditions let you extract a field only when a condition is true. For example, only add a "PRIORITY" prefix when the invoice amount exceeds $10,000. If the condition is false, the field is skipped.

Fallback Chains define multiple extraction attempts when extraction might fail. For example: first try "Extract company name from letterhead", then "from signature block", then "any company name mentioned". The first successful extraction wins. If all fail, a default value is used.

Computed Fields derive values from other fields without additional AI calls. For example, concatenate first_name and last_name into a Full Name field.

Template Rules#

Template Rules apply business logic during filename generation. They are different from file organization Rules — Template Rules modify the naming process, not file locations. Each rule has a condition (when it applies), an action (what happens), and timing (when in the process it runs).

Example: Priority Invoice Prefix

Add "PRIORITY-" to invoices over $10,000:

• Condition: invoice_amount is greater than 10000
• Action: Add prefix "PRIORITY-"

Result: PRIORITY-2024-03-15_Amazon_INV-4711.pdf

Example: Skip Field When Empty

Don't include purchase order number if it doesn't exist:

• Condition: po_number is empty
• Action: Skip field

Use Template Rules for naming logic. Use Document Rules for file organization.

Automation#

FAQ#

Can I convert a Custom Prompt to a Template? Not automatically, but you can use a Custom Prompt to understand what structure works for your files, then create a Template with those fields.

What if the AI can't extract a field? If a required field is missing, the rename is blocked to prevent incomplete filenames. Use fallback chains or mark fields as optional to handle edge cases.

Do text cleanups use AI? Text cleanups are sent as instructions to the AI alongside extraction. They're processed in the same API call, not separately.

Can I use both AI fields and system placeholders? Yes. Mix them freely: {Vendor Name}_{date}_{Invoice Number}