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docs: update intro sentence
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README.md

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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)
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[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE)
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**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.
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**Token-Oriented Object Notation** is a compact, human-readable encoding of the JSON data model for LLM prompts. It provides a lossless serialization of the same objects, arrays, and primitives as JSON, but in a syntax that minimizes tokens and makes structure easy for models to follow.
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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.
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- [Key Features](#key-features)
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- [When Not to Use TOON](#when-not-to-use-toon)
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- [Benchmarks](#benchmarks)
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- [Playgrounds](#playgrounds)
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- [📋 Full Specification](https://github.com/toon-format/spec/blob/main/SPEC.md)
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- [Installation & Quick Start](#installation--quick-start)
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- [Playgrounds](#playgrounds)
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- [CLI](#cli)
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- [Format Overview](#format-overview)
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- [API](#api)
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- [Using TOON in LLM Prompts](#using-toon-in-llm-prompts)
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- [Notes and Limitations](#notes-and-limitations)
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- [Syntax Cheatsheet](#syntax-cheatsheet)
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- [Other Implementations](#other-implementations)
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- [📋 Full Specification](https://github.com/toon-format/spec/blob/main/SPEC.md)
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## Why TOON?
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