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52 lines
1.7 KiB
Markdown
52 lines
1.7 KiB
Markdown
---
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layout: home
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hero:
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name: TOON
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text: Token-Oriented Object Notation
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tagline: A compact, human-readable encoding of the JSON data model for LLM prompts.
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image:
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dark: /logo-index-dark.svg
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light: /logo-index-light.svg
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alt: TOON Logo
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actions:
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- theme: brand
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text: Get Started
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link: /guide/getting-started
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- theme: alt
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text: Benchmarks
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link: /guide/benchmarks
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- theme: alt
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text: CLI
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link: /cli/
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- theme: alt
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text: Spec v2.0
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link: /reference/spec
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features:
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- title: Token-Efficient & Accurate
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icon: 📊
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details: TOON reaches 74% accuracy (vs JSON's 70%) while using ~40% fewer tokens in mixed-structure benchmarks across 4 models.
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link: /guide/benchmarks
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- title: JSON Data Model
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icon: 🔁
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details: Encodes the same objects, arrays, and primitives as JSON with deterministic, lossless round-trips.
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link: /guide/format-overview
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- title: LLM-Friendly Guardrails
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icon: 🛤️
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details: Explicit [N] lengths and {fields} headers give models a clear schema to follow, improving parsing reliability.
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link: /guide/format-overview#arrays
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- title: Minimal Syntax
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icon: 📐
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details: Uses indentation instead of braces and minimizes quoting, giving YAML-like readability with CSV-style compactness.
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link: /guide/format-overview#arrays
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- title: Tabular Arrays
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icon: 🧺
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details: Uniform arrays of objects collapse into tables that declare fields once and stream row values line by line.
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link: /guide/format-overview#arrays
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- title: Multi-Language Ecosystem
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icon: 🌐
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details: Spec-driven implementations in TypeScript, Python, Go, Rust, .NET, and other languages.
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link: /ecosystem/implementations
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---
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