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docs: refine intro description

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Johann Schopplich
2025-11-14 18:26:46 +01:00
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[![npm downloads (total)](https://img.shields.io/npm/dt/@toon-format/toon.svg)](https://www.npmjs.com/package/@toon-format/toon) [![npm downloads (total)](https://img.shields.io/npm/dt/@toon-format/toon.svg)](https://www.npmjs.com/package/@toon-format/toon)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE) [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE)
**Token-Oriented Object Notation** is a compact, human-readable serialization format designed for passing structured data to Large Language Models with significantly reduced token usage. It's intended for *LLM input* as a lossless, drop-in representation of JSON data. **Token-Oriented Object Notation** is a compact, human-readable format for serializing JSON data in LLM prompts. It represents the same objects, arrays, and primitives as JSON, but in a syntax that minimizes tokens and makes structure easy for models to follow.
TOON's sweet spot is **uniform arrays of objects** – multiple fields per row, same structure across items. It borrows YAML's indentation-based structure for nested objects and CSV's tabular format for uniform data rows, then optimizes both for token efficiency in LLM contexts. For deeply nested or non-uniform data, JSON may be more efficient. TOON combines YAML's indentation-based structure for nested objects with a CSV-style tabular layout for uniform arrays. TOON's sweet spot is **uniform arrays of objects** (multiple fields per row, same structure across items), achieving CSV-like compactness while adding explicit structure that helps LLMs parse and validate data reliably. For deeply nested or non-uniform data, JSON may be more efficient.
TOON achieves CSV-like compactness while adding explicit structure that helps LLMs parse and validate data reliably. Think of it as a translation layer: use JSON programmatically, convert to TOON for LLM input. The similarity to CSV is intentional: CSV is simple and ubiquitous, and TOON aims to keep that familiarity while remaining a lossless, drop-in representation of JSON for Large Language Models.
Think of it as a translation layer: use JSON programmatically, and encode it as TOON for LLM input.
> [!TIP] > [!TIP]
> TOON is production-ready, but also an idea in progress. Nothing's set in stone – help shape where it goes by contributing to the [spec](https://github.com/toon-format/spec) or sharing feedback. > TOON is production-ready, but also an idea in progress. Nothing's set in stone – help shape where it goes by contributing to the [spec](https://github.com/toon-format/spec) or sharing feedback.