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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.
 
-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.
+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.
 
 The similarity to CSV is intentional: CSV is simple and ubiquitous, and TOON aims to keep that familiarity while remaining a lossless, drop-in representation of JSON for Large Language Models.