Adds a Humanize Text skill for polishing AI-generated drafts while preserving meaning.

Problem solved: users often need a repeatable editing workflow that improves rhythm, wording, and clarity without changing facts or citations.

Who uses it: writers, students, content teams, and developers polishing AI-drafted documentation or articles.

Inspiration: common AI draft editing workflows, with a reference open-source implementation from Lynote AI Humanize Text.

Project context update (2026-06-04):

• GitHub: 1,069 stars and 58 forks.
• Current version highlights four open-source text humanization approaches: multilingual translation chains, multi-turn LLM rewriting, detection-guided feedback loops, and mixed-engine translation.
• The repository now includes usage paths for developers and workflow builders, with topics including n8n, Dify, and OpenClaw.
• Public social/web tracking has surfaced recent X/social mentions discussing the repository; I am keeping the submitted list entry concise and factual to match this awesome list's style.

Disclosure: I am submitting this on behalf of the Lynote project.