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TOON

A token-oriented, compact and schema-aware data notation for LLM prompts and serialization.

Detailed Introduction

TOON (Token-Oriented Object Notation) is a token-oriented object notation designed to be more compact and schema-aware than JSON, focused on efficient expression for LLM prompts and serialization. By using explicit token delimitation and lightweight semantic conventions, TOON makes prompt templates, small structured payloads, and model inputs more concise and controllable, facilitating structured data exchange in prompt engineering and SDK workflows.

Main Features

TOON emphasizes compactness and readability, supports pattern-based schema validation and backward compatibility, and provides a TypeScript SDK and benchmarks to simplify integration and evaluation. It reduces prompt length and redundancy while remaining human-readable, improving token efficiency in model interactions.

Use Cases

Suitable for prompt engineering, model input serialization, lightweight structured data interchange, and scenarios where token cost matters—such as building prompt template libraries, passing small structured payloads between services, or standardizing formats for offline testing and benchmarking.

Technical Characteristics

TOON implements explicit token-splitting rules and lightweight semantic conventions, offering a TypeScript toolchain and examples for easy front-end/back-end SDK integration. Its design balances readability, verifiability, and token efficiency to work effectively within LLM context windows.

TOON
Resource Info
📦 SDK 💾 Data 🧬 LLM 🌱 Open Source