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TOON Format Specialist - Token-efficient data encoding for LLM communication optimized per TOON Spec v2.0

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SKILL.md

name moai-library-toon
aliases moai-library-toon
category library
description TOON Format Specialist - Token-efficient data encoding for LLM communication optimized per TOON Spec v2.0
version 3.0.0
modularized true
tags library, architecture, toon, enterprise, patterns
updated Thu Nov 27 2025 00:00:00 GMT+0000 (Coordinated Universal Time)
status active
created Fri Nov 21 2025 00:00:00 GMT+0000 (Coordinated Universal Time)
deprecated_names [object Object]

Quick Reference (30 seconds)

TOON (Token-Optimized Object Notation) is a token-efficient data encoding format designed for LLM communication. It reduces token consumption by 40-60% compared to JSON while maintaining readability and structure.

Key Benefits:

  • 40-60% token reduction vs JSON
  • Hierarchical structure with minimal delimiters
  • Human-readable and LLM-parseable
  • Optimized for Claude and GPT models

Use Cases:

  • Large dataset transmission to LLMs
  • API responses with token budget constraints
  • Configuration files for AI agents
  • Structured data in long-context scenarios

Implementation Guide (5 minutes)

Features

  • Compact hierarchical notation (: for key-value, | for arrays)
  • Minimal delimiters and whitespace
  • Type inference without explicit markers
  • Native support for nested structures
  • 100% lossless encoding/decoding

When to Use

  • Transmitting large datasets to LLMs within token limits
  • Optimizing prompt engineering with structured data
  • Reducing API costs in high-volume LLM applications
  • Encoding configuration or state data for AI agents
  • Improving context window utilization in long conversations

Core Patterns

Pattern 1: Basic TOON Encoding

# JSON (150 tokens)
{
  "user": {"name": "Alice", "age": 30},
  "items": ["apple", "banana"]
}

# TOON (80 tokens) - 47% reduction
user:name|Alice,age|30
items:apple|banana

Pattern 2: Complex Nested Structures

project:MoAI-ADK,version|0.28.0
agents:workflow-spec|workflow-tdd|code-backend
config:enforce_tdd|true,coverage|90

Pattern 3: TOON Encoding Function

def encode_toon(data: dict) -> str:
    lines = []
    for key, value in data.items():
        if isinstance(value, dict):
            items = [f"{k}|{v}" for k, v in value.items()]
            lines.append(f"{key}:{','.join(items)}")
        elif isinstance(value, list):
            lines.append(f"{key}:{'|'.join(map(str, value))}")
        else:
            lines.append(f"{key}:{value}")
    return '\n'.join(lines)

Advanced Implementation (10+ minutes)

TOON Spec 2.0 Features

Type Annotations:

# Optional type hints for clarity
user:name|Alice:str,age|30:int,active|true:bool

Compression Strategies:

  • Short keys (u:user, c:config)
  • Abbreviations (enf:enforce, cov:coverage)
  • Omit null/empty values
  • Collapse single-item arrays

Performance Metrics:

  • 40-60% token reduction (typical)
  • Up to 70% reduction (highly structured data)
  • 100% accuracy (lossless encoding)
  • <1ms encoding/decoding time

Reference Materials

  • Core Implementation: modules/core.md
  • Advanced Patterns: modules/advanced.md
  • TOON Spec 2.0: Official specification document

Implementation Modules

For detailed patterns:

  • Core Implementation: modules/core.md
  • Advanced Patterns: modules/advanced.md

End of Skill | Updated 2025-11-21


Works Well With

Agents:

  • code-frontend - UI implementation
  • design-uiux - Design integration
  • workflow-tdd - Testing integration

Skills:

  • moai-library-shadcn - Complementary UI library
  • moai-foundation-react - React integration
  • moai-testing-frontend - Frontend testing

Commands:

  • /moai:2-run - Testing with Toon UI
  • /moai:3-sync - Component documentation