Text & Prompt Optimizer

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Reduces token consumption and improves LLM instruction quality through automated text compression and structural optimization.

The Text Optimizer skill is a specialized tool for Claude Code designed to maximize token efficiency and model performance by applying 41 research-backed rules to prompts, documentation, and agent instructions. It offers three distinct modes—Light, Medium, and Deep—allowing users to choose between simple text cleanup and aggressive structural rephrasing that can reduce token counts by 20–40%. By optimizing Claude's behavior, improving reference integrity, and enhancing structural clarity using XML tags and imperative language, this skill helps developers create cheaper, faster, and more accurate AI-driven workflows while minimizing hallucinations.

Características Principales

01Structural enhancements using XML tags, tables, and imperative formatting
02Three processing modes (Light, Medium, Deep) for varying levels of compression
03Validation of file paths, URLs, and cross-references to ensure integrity
04Automated token reduction of 20–40% without losing original meaning
0541 research-backed optimization rules across 6 specific categories
0616 GitHub stars

Casos de Uso

01Optimizing Claude agent skills and instructions for faster model response times
02Refining complex system prompts to reduce API costs and improve instruction following
03Compressing long documentation files to fit within LLM context windows