toon and ZON
These are competitors: both aim to reduce LLM prompt costs through schema-aware serialization, but ZON claims superior compression efficiency (35-70% savings) compared to TOON's token optimization approach.
About toon
toon-format/toon
🎒 Token-Oriented Object Notation (TOON) – Compact, human-readable, schema-aware JSON for LLM prompts. Spec, benchmarks, TypeScript SDK.
Combines YAML-style indentation with CSV-like tabular layouts for uniform arrays, achieving ~40% token savings over JSON while maintaining lossless round-trip conversion. The format uses explicit array-length declarations `[N]` and field headers `{fields}` to provide LLMs with clear schema boundaries, improving both parsing accuracy (74% vs JSON's 70%) and reliability. Spec-driven with implementations across TypeScript, Python, Go, Rust, and .NET, designed as a translation layer between JSON-based application logic and token-efficient LLM input.
About ZON
ZON-Format/ZON
ZON → 35-70% cheaper LLM prompts than JSON/TOON. Zero overhead.
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