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toon-formatter

Convert structured data arrays, tables, and logs into TOON v2.0 format.

Updated Jan 2, 2026
Search Tags:#structured data#data transformation#token optimization#AI processing#TOON v2.0
One-click install
npx skills add https://github.com/cooopmac/nourish --skill toon-formatter-cooopmac
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: toon-formatter
Source: https://github.com/cooopmac/nourish/tree/main/.claude/project/skills/toon-formatter
Command: npx skills add https://github.com/cooopmac/nourish --skill toon-formatter-cooopmac

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The toon-formatter Skill addresses the challenge of efficiently handling large amounts of structured data by converting it into the TOON v2.0 format, reducing token consumption and optimizing AI processing.

Core Features & Use Cases

  • TOON v2.0 Conversion: Automatically transform data arrays, tables, logs, and API responses into TOON v2.0 format.
  • Custom Encoding: Support for 3 array types (inline, tabular, expanded) and 3 delimiters (comma, tab, pipe).
  • Key Folding: Flatten nested objects to save additional tokens.
  • Use Case: Ideal for AI systems where structured data processing is required, such as RAG pipelines, benchmarks, and analytics.

Quick Start

Convert the data array provided into TOON v2.0 format and display the result.

Frequently Asked Questions about toon-formatter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce token consumption when processing structured data for AI?▼

To reduce token consumption for structured data, you can convert arrays, tables, and logs into TOON v2.0 format. This transformation flattens nested objects and optimizes encoding to minimize the token count processed by AI systems.

What is TOON v2.0 format and when should I use it for data transformation?▼

TOON v2.0 format is an encoding method for structured data that reduces token usage. You should use it when processing arrays, tables, or API responses in AI pipelines, such as RAG implementations, benchmarks, and analytics tasks.

Can I use custom delimiters and array types when converting structured data to TOON v2.0?▼

Yes, converting structured data to TOON v2.0 supports custom encoding with three array types (inline, tabular, expanded) and three delimiters (comma, tab, pipe). This flexibility allows you to tailor the data transformation to your specific parsing needs.

What is the best way to flatten nested objects in API responses for RAG pipelines?▼

The best way to flatten nested objects in API responses for RAG pipelines is using key folding during TOON v2.0 conversion. This technique flattens the data structure directly, saving additional tokens before the data enters the AI processing stage.

Does token optimization for structured data work with log files and tabular data?▼

Yes, token optimization for structured data works effectively with log files and tabular data. The TOON v2.0 conversion process supports multiple data types and delimiters, specifically targeting arrays, tables, and logs to reduce token consumption.

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