text-optimizer
Reduces token count in prompts and docs by 20–40% using 41 research-backed optimization rules.
- Applies rules across six categories: Claude behavior, token efficiency, structure, reference integrity, perception, and LLM comprehension
- Three optimization modes: light (text cleanup only), medium (balanced restructuring, default), and deep (aggressive compression and rephrasing)
- Processes single files or entire directories of markdown files, with built-in quality checks for reference validity and information preservation
- Generates optimization reports showing token reduction metrics and which rules were applied to each file
Plugin: kochetkov-ma/claude-brewcode
Text Optimizer
Reduces token count in prompts, docs, and agent instructions by 20–40% without losing meaning. Applies 41 research-backed rules across 6 categories: Claude behavior, token efficiency, structure, reference integrity, perception, LLM comprehension.
Benefits: cheaper API calls · faster model responses · clearer LLM instructions · fewer hallucinations
Examples:
/text-optimize prompt.md # single file, medium mode (default)
/text-optimize -d agents/ # deep mode — all .md files in directory
Skill text is written for LLM consumption and optimized for token efficiency.
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