toon

You can reduce token cost by converting JSON data into Token-Oriented Object Notation (TOON), a compact, indentation-based format that minimizes tokens while preserving the original data model for LLM input.

The best way to serialize structured data for LLM parsing accuracy is using a token-efficient format with indentation-based structure and CSV-style tabular arrays, which helps LLMs parse uniform data reliably.

Yes, converting JSON to TOON supports lossless round-trips, meaning the encoded data can be fully restored to its original JSON structure without losing any information during the serialization process.

To encode a JSON file into TOON format, process the attached JSON file through the conversion skill, which outputs a human-readable, token-optimized representation ready for LLM analysis.

TOON provides greater token efficiency than YAML and JSON, using indentation and tabular arrays to significantly reduce token count and lower API costs while maintaining data integrity.

You should avoid compact data formats if your downstream system strictly requires raw JSON or lacks a deserialization mechanism to decode the TOON structure back into standard JSON.