Reduces LLM token usage by converting structured data into a compact, header-based format for significant cost savings.
Sponsored
Toon implements the Token-Oriented Object Notation (TOON), a compact data format specifically designed to optimize input for Large Language Models (LLMs). By using a header-based approach that avoids repeating field names for every object, it dramatically reduces token count by 50-70% compared to traditional JSON, leading to substantial cost savings when processing structured data with LLMs. It offers functionalities to encode various data formats to TOON, decode TOON back to JSON, analyze potential token savings, and automatically optimize data sections within prompts.
Key Features
01Convert JSON, CSV, TSV, XML, HTML tables, and YAML to TOON format
02Decode TOON data back to JSON
03Analyze potential token and cost savings for given data
04Automatically optimize data sections within LLM prompts for efficiency
05Programmatic API for Node.js integration
062 GitHub stars
Use Cases
01Optimizing LLM token usage for arrays of objects with consistent structures
02Reducing costs when sending large API responses or database results to LLMs
03Improving efficiency for prompts containing extensive structured data
04Integrating compact data format into Claude Desktop/Code via MCP server
