text-optimizer

Reduces token count in prompts and docs by 20–40% using 41 research-backed optimization rules. Plugin: kochetkov-ma/claude-brewcode 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: Skill text is written for LLM consumption and optimized for token efficiency. REQUIRED: Read references/rules-review.md before ANY optimization. If file not found -> ERROR + STOP. Do not proceed without rules reference. Parse $ARGUMENTS : -l / --light | -d / --deep | no flag -> medium (default).