TOON

TOON is a data serialization format that encodes JSON structures into a compact, human-readable syntax specifically designed for LLM prompts.

TOON, or Token-Oriented Object Notation, provides an alternative to standard JSON serialization for large language model prompts. It encodes objects, arrays, and primitives using indentation and minimal quoting to achieve CSV-style compactness with YAML-like readability. The format implements guardrails that allow users to declare row counts and field widths, which prevents the processing of truncated or malformed outputs. TOON ensures deterministic, lossless round-trips for data. It supports a multi-language ecosystem with an official specification and a shared conformance test suite.

TOON at a glance

Best for: Software engineer
Pricing: Free
Released: October 2025
Category: AI coding tool
Website: toonformat.dev

Key features

Reduces token usage by 42.6% compared to JSON
Uses indentation to replace braces for compact syntax
Implements row count and field width declarations
Maintains lossless round-trips for JSON data models
Includes a shared conformance test suite for community ports

Use it for

Compressing JSON data for LLM prompts
Validating structured output with guardrails
Reducing prompt costs in language model workflows

Alternatives to TOON

LangChain4j — Integrates LLMs and vector stores directly into Java applications.
Lcc — Cuts token counts significantly without losing exact session details.
Langfa.st — Compare model responses side-by-side to validate prompts before deployment.
MTPLX — It runs local models twice as fast via native MTP speculative decoding.
llm-d — Deploys production-grade LLM serving on existing hardware clusters.
LMQL — It enables modularized, constraint-based prompting with portable code.
OpenCode — Works with 75+ model providers, local models, and existing subscriptions
LightLLM — It delivers high-speed inference and serving performance for large language models.
WebLLM — Runs high-performance language models directly inside web browsers.
RTK — Reduces AI context output noise by 56 to 90 percent with zero configuration.
LangChain — Compose exactly the agent your use case needs from model, tools, prompt, and middleware.
Sjq — Read AI streaming data without the repetitive envelope overhead.

All TOON alternatives