JSONToTable

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How to Convert JSON to TOON - Step by Step Guide

Step 1

Input Your JSON Data

Start by inputting your JSON data that you want to convert to TOON format. TOON (Token-Oriented Object Notation) is specifically designed for LLM prompts and can reduce token usage by up to 50%:

•
Paste directly: Copy your JSON data and paste it into the input editor
•
Upload a file: Click "Upload" to select a .json file from your computer
•
Try the sample: Click "Sample" to load example data and see the conversion in action

Example: JSON Input

Here's sample JSON data to convert:

{
  "users": [
    {
      "id": 1,
      "name": "Alice",
      "role": "admin"
    }
  ]
}
Step 2

Automatic Conversion to TOON

The conversion happens automatically! As soon as you input valid JSON, the tool converts it to TOON format with significant benefits:

•
50% fewer tokens: TOON format uses approximately half the tokens compared to JSON
•
Tabular format: Arrays of objects are displayed in a compact, table-like format
•
LLM-friendly: Self-documenting structure that models parse naturally

Example: TOON Output

The same data in TOON format - notice how compact it is:

users[1]{id,name,role}:
  1,Alice,admin
Step 3

Choose Delimiter Options

Customize how your TOON data is formatted by choosing the delimiter that best suits your needs:

•
Comma (default): Standard delimiter for most use cases
•
Tab delimiter: Better token efficiency for large uniform tables
•
Pipe delimiter: Middle ground between comma and tab
Step 4

Export Your TOON Data

Get your converted TOON data ready for use in your LLM prompts:

•
Copy to clipboard: One-click copying for quick pasting into your LLM prompt
•
Download as file: Save as a .toon file for later use
•
Real-time conversion: See the results instantly as you type

Frequently Asked Questions

What is TOON format and why should I use it?

TOON (Token-Oriented Object Notation) is a data format designed specifically for LLM prompts. It reduces token usage by approximately 50% compared to JSON while maintaining readability. This means lower API costs and the ability to fit more data in your prompts. The format uses explicit length markers like [N] and field headers like {field1,field2} to create self-documenting structure. Learn more at the official TOON GitHub repository or visit toonformat.dev.

When should I use TOON instead of JSON?

TOON excels with uniform arrays of objects (same fields, primitive values), especially large datasets with consistent structure. Use JSON for non-uniform data, deeply nested structures, and objects with varying field sets. TOON is ideal for LLM inputs where token efficiency matters.

Which delimiter should I choose?

For most cases, comma (default) works well. Use tab delimiter for large uniform tables as tabs often tokenize better and reduce quote-escaping needs. Pipe delimiter offers a middle ground and is useful when your data contains many commas.

Can I convert TOON back to JSON?

Yes! TOON is fully reversible. The format is self-documenting with explicit structure (length markers, field headers) that makes it easy to convert back to JSON without data loss. The official library provides both encode() and decode() functions for bidirectional conversion.

Does TOON work with all LLMs?

Yes! TOON's structure is self-documenting and models parse it naturally once they see the pattern. It works with GPT models, Claude, and other major LLMs. The explicit length markers [N] and field headers help the model track structure reliably.

Is the JSON to TOON converter free?

Yes, completely free with no limitations on file size, usage frequency, or features. No registration required, and you can convert unlimited JSON files to TOON format. Also check out our JSON formatter and JSON validator tools.

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