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moai-formats-data

Optimize data formats for LLM communication with TOON encoding and JSON/YAML serialization.

3|Updated Feb 18, 2026
Search Tags:#data validation#data optimization#TOON encoding#LLM communication#JSON optimization#YAML optimization
One-click install
npx skills add https://github.com/rodmena-limited/trust5 --skill moai-formats-data-rodmena-limited
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: moai-formats-data
Source: https://github.com/rodmena-limited/trust5/tree/main/trust5/assets/claude/skills/moai-formats-data
Command: npx skills add https://github.com/rodmena-limited/trust5 --skill moai-formats-data-rodmena-limited

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires orjson, PyYAML, ijson, python-dateutil, regex, jsonschema, cerberus, marshmallow, pydantic, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill specializes in optimizing data for transmission to LLMs, providing high-performance serialization, and ensuring data validation for modern applications.

Core Features & Use Cases

  • TOON Encoding: Significantly reduces token usage for LLM communication (40-60% reduction vs JSON).
  • JSON/YAML Optimization: Achieves efficient serialization and parsing, ideal for large datasets and high-performance APIs.
  • Data Validation: Enforces schema validation, type checking, and error handling for data integrity.
  • Use Case: When you need to optimize data for LLMs within a token budget, implement high-performance serialization, validate data schemas, or convert between data formats.

Quick Start

To encode data for LLM optimization, create a TOONEncoder instance and call encode with a dictionary. For fast JSON processing, use a JSONOptimizer instance with serialize_fast. For data validation, create a DataValidator instance and call validate with the data and schema.

Frequently Asked Questions about moai-formats-data

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

FAQPage Schema
How do I reduce token usage when sending JSON data to LLMs?▼

TOON encoding reduces token usage for LLM communication by 40-60% compared to JSON. Create a TOONEncoder instance and call the encode method with a dictionary to compress your data payload before transmission.

What is the best way to optimize YAML serialization for large datasets?▼

YAML optimization for large datasets is achieved through efficient serialization and parsing patterns. Use a dedicated JSONOptimizer instance with the serialize_fast method to process high-performance APIs and large data structures.

Does this data validation approach work with Pydantic and Marshmallow?▼

Data validation supports schema enforcement and type checking using Pydantic and Marshmallow. Create a DataValidator instance and call the validate method with your data and schema to ensure data integrity and handle errors.

Can I use orjson for fast JSON processing within Claude Code?▼

Fast JSON processing within Claude Code requires orjson as a dependency. The Skill utilizes orjson alongside ijson to achieve high-performance serialization and parsing for modern applications and large datasets.

When do I need Cerberus or jsonschema for data validation?▼

You need Cerberus and jsonschema when enforcing strict schema validation and type checking for data integrity. These dependencies support the DataValidator instance to ensure complex data structures conform to specified schemas.

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