Rewrite Chinese communication copy to sound natural and human.
npx skills add https://github.com/TianyiDataScience/humanize --skill humanize-tianyidatascience
Please help me install this Agent Skill. Skill: humanize Source: https://github.com/TianyiDataScience/humanize/tree/main Command: npx skills add https://github.com/TianyiDataScience/humanize --skill humanize-tianyidatascience
This Skill eliminates the issue of Chinese communication copy feeling templated, robotic, and overly polished by AI, transforming it into natural, human-sounding messages that preserve all original meaning and required facts.
Use the humanize skill to rewrite the provided Chinese customer service reply to sound more natural and less templated, keeping all key details including the tomorrow afternoon timeline and finance team reference.
High-intent search queries and answers about installing and using this skill.
To make AI generated Chinese customer service replies sound natural, the humanize skill applies an iterative optimization loop with local scoring to eliminate robotic phrasing while preserving required facts like timelines and team references. It enforces hard constraints for length limits and banned template language.
The best way to humanize Chinese copy for self-media content and community notifications is using an iterative candidate generation workflow with repair loops. This local scoring approach continuously improves copy quality by matching natural human messaging patterns across various communication scenarios.
Yes, you can use this text humanization skill with Claude Code, CoPaw, OpenClaw, and Hermes AI agent platforms. It supports integration with any AI agent platform that can execute local shell commands, enabling seamless workflow automation for Chinese communication optimization.
Yes, the Chinese copywriting humanization tool supports both generate mode and rewrite mode. Generate mode creates new copy from a task description, while rewrite mode optimizes existing user drafts to eliminate overly AI-polished phrasing and match natural human messaging patterns.
The local scoring mechanism works by generating multiple candidate texts, scoring them against natural human messaging patterns, and applying repair loops for failures. It provides full transparent process output showing baseline scores, candidates, failure tags, and selection rationale for complete user visibility.
Yes, when humanizing AI text for after-sales communications, the tool enforces hard constraints for required phrases, length limits, and banned template language. These constraints ensure the optimized copy preserves all original meaning and required facts while sounding completely natural.
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