OwnPen AI Trace Removal Rewrite

Problem: “AI tone” in Chinese prose is a pattern issue

Many drafts read correctly sentence by sentence but feel templated overall: openers like “In today’s...”, buzzwords such as “empower,” “closed loop,” and “handle,” and closers like “In summary.” These are not grammar errors, but they make articles, reports, and resumes look machine-generated. The core issue spans vocabulary, syntax, structure, and flat emotional rhythm. Asking a model simply to “make it fluent” often keeps the same scaffolding.

How It Works: Scene-First Editing and Rule-Guided Rewriting

OwnPen splits the task into two modes: rewrite and diagnose. Before rewriting, it asks for a scene such as general, WeChat article, Zhihu, Xiaohongshu, work report, business email, short-video script, product copy, or resume. Each scene has a concrete target: reports lead with the conclusion, emails remove bureaucratic tone, scripts control line length and pauses, and resumes replace generic traits with specific experience. It applies built-in rules to flag severe, obvious, and minor issues, including buzzword stacking, triple parallelism, thesis-body-conclusion structure, no clear stance, and forced positivity. Output keeps the original stance and format, avoids adding boxes, symbols, or labels, and lists the main changes. Diagnose mode reports issue locations, severity levels, and an “AI-smell index.”

Boundaries: A Style Constraint, Not a Fact Generator

It works best on existing Chinese drafts that need de-templating, not on generating long content from scratch or adding missing facts. It preserves core claims and does not invent examples or numbers; when concrete experience is missing, it suggests supplementation. For academic rigor, legal compliance, or brand voice control, human review is still required. It addresses the expressional layer of “does this sound human,” not factual validation or business judgment.