Professional TOON Formatter

TOON Formatter & Validator

Format, validate, and work with Token-Oriented Object Notation (TOON) data. Our free online tool helps you format, validate, and convert TOON data with syntax highlighting and error detection.

TOON Syntax Reference

[N]Tabular Array

Starts an array of N items, followed by a header row {key1,key2}

key: valueObject Property

Standard key-value pair. Indent for nested objects.

Powerful TOON Formatting Features

Convert JSON to token-efficient TOON format

Convert TOON back to standard JSON

Visualize token savings instantly

Tabular formatting for array data

Syntax highlighting for both formats

Client-side processing for privacy

One-click copy and download

Format validation and error checking

Support for nested objects and arrays

Optimized for GPT-4, Claude, and other LLMs

What is Token-Oriented Object Notation (TOON)?

Token-Oriented Object Notation (TOON) is a modern data format optimized for Large Language Models (LLMs). It addresses the verbosity of JSON by removing redundant syntax characters (like quotes, commas, and braces) and using a tabular layout for arrays. This results in a format that consumes significantly fewer tokens while remaining human-readable.

Understanding TOON Syntax

TOON uses a clean, whitespace-sensitive syntax. Here are the key elements:

Tabular Arrays

Arrays of objects are where TOON saves the most tokens. Instead of repeating keys for every object, TOON declares the keys once in a header.

users: 
[3]
  {id,name,role}
  1,"Alice","Admin"
  2,"Bob","User"
  3,"Charlie","User"
In this example:
  • [3] indicates an array with 3 items.
  • {id,name,role} defines the keys for the objects.
  • Subsequent lines contain the values for each object, separated by commas.

Clean Objects

Standard objects use simple key-value pairs with indentation to show nesting.

config: 
  env: "production"
  retries: 3
  features: 
    logging: true
    analytics: false

Benefits of Using TOON

Significant Token Savings

By eliminating repetitive keys and syntax, TOON can reduce the token count of your data by 30-60%. This directly translates to lower API costs when using models like GPT-4 or Claude.

Enhanced Context Window

LLMs have a fixed context window. Using TOON allows you to fit more data (e.g., longer search results, larger datasets) into a single prompt without hitting the limit.

Improved Model Performance

The structured, tabular nature of TOON is easy for LLMs to parse. It mimics the CSV-like or markdown-table formats that models are well-trained on, often leading to better understanding and retrieval accuracy.

Common TOON Use Cases

RAG (Retrieval-Augmented Generation)

When feeding retrieved documents or data into an LLM, converting them to TOON first allows you to include more context and reduces the cost of every query.

Large Data Exports

For exporting large lists of users, products, or logs, TOON's tabular format is much more compact than JSON lines or standard JSON arrays.

Configuration and Prompts

Writing complex system prompts or configurations in TOON can save tokens and make the prompt easier for the developer to read and edit.

Why Choose Our TOON Formatter?

Frequently Asked Questions
What is Token-Oriented Object Notation (TOON)?

Token-Oriented Object Notation (TOON) is a data interchange format designed specifically for Large Language Models (LLMs). It minimizes token usage by removing repetitive syntax like quotes, brackets, and repeated keys in arrays, replacing them with a tabular structure and indentation.

How does TOON save tokens?

TOON saves tokens by defining keys only once for arrays of objects (in a header row) instead of repeating them for every item. It also removes structural characters like curly braces and commas, using newlines and indentation instead. This can reduce token count by 30-60%.

Can I convert between TOON and JSON?

Yes, our TOON formatter supports bidirectional conversion. You can paste JSON to convert it to the token-efficient TOON format, or paste TOON data to convert it back to standard JSON for use in your applications.

Is TOON human-readable?

Yes, TOON is designed to be highly readable. Its tabular format for data lists and indented structure for objects makes it look similar to YAML or a spreadsheet, which is often easier for humans to scan than raw JSON.

Why use TOON for LLMs?

LLMs have context window limits and charge per token. Using TOON allows you to fit more data into the context window and reduces API costs. It also provides a structured format that models like GPT-4 are good at parsing.

How do I validate TOON data?

Our tool includes a validator that checks if your TOON data follows the correct structure (tabular arrays, proper indentation). Simply paste your data and the tool will highlight any issues.

💡 Pro Tips

Ready to Get Started?

Choose from our suite of JSON tools to start processing your data right away.